Category: DevOps Toolbox

Multi-Cloud Computing is a Major IT Headache

A CloudBolt Software survey of 500 senior IT, DevOps, security and finance leaders found 79% are struggling under the weight of managing multiple cloud computing environments.

The survey from CloudBolt Software, a provider of a cloud management platform, found specifically that more than three-quarters of respondents (78%) said they have too many cloud tools throughout their enterprise, and 80% struggled to achieve comprehensive visibility into cloud usage and spending. A total of 80% also noted that their current approach to cloud computing created new security vulnerabilities.

A full 88% said they need a “manager of managers” that would enable them to unify the various silos that have multiplied across their IT environment.

Nevertheless, 78% of respondents said that moving to the cloud enabled them to achieve cost savings compared to running applications in an on-premises IT environment.

CloudBolt Software CEO Jeff Kukowski said the issue is not so much that IT organizations regret shifting workloads to the cloud; instead, the issue is finding a way to manage multiple clouds, each with their own set of tools and frameworks that need to be mastered.

It’s not clear whether organizations are deliberately employing multiple clouds or if, because of simple inertia, they have found themselves managing multiple cloud platforms because of decisions made by various development teams. Some IT organizations, for example, employ multiple clouds because they are concerned about either becoming locked into a specific cloud computing service or whether an outage might take all their applications offline at the same time. Others are simply trying to take advantage of services that are better provided by one vendor than another.

Regardless of how IT organizations found themselves managing multiple clouds, the total cost of IT rises as each new platform is added to an IT environment. CloudBolt Software is making a case for an IT framework that provides a layer of abstraction through which the management of multiple clouds and on-premises IT environments can be unified. It is more a question of time and degree to which IT organizations will eventually consolidate the management of disparate IT environments under a single control plane that provides the foundation for true hybrid cloud computing, said Kukowski.

There are, of course, a few organizations that have standardized on a single cloud computing platform. The degree to which those organizations can maintain that standard will naturally vary as, for example, new workloads that may be optimized for a specific cloud environment are built or as companies acquire other organizations that are running workloads on other cloud platforms. In many of those cases, organizations discover that the cloud services invoked expose a range of proprietary application programming interfaces (APIs) and disparate virtual machines that make migrating workloads a major challenge.

Like it or not, most organizations will be managing multiple IT environments for the foreseeable future. The only thing that is uncertain is the volume of workloads that might be running on any one of those platforms at any given time.

March 1, 2022

SQL Server MDF to NDF Distribution

Do you have massive MDF files on your database? Have you noticed that your SQL Server disk stall metrics for these data files are higher than the storage latency metrics exhibited on the underlying operating system? It could be that your SQL Server data files are being hammered too hard and you don’t have enough data files to help the SQL Server storage engine distribute the load. We do this for tempdb, right? Let’s do this for our user databases as well. It’s easy for a brand-new database. But existing databases may be out of control with a single data file. Let me show you how to adjust this for existing databases without an outage!

I’ll be taking the SQL Server database generated by the HammerDB benchmark, appropriately named tpcc_test. It’s just a backed-up-and-restored copy of the (appropriately named) database tpcc_single to represent a single MDF file present.

I did a restore onto the F: drive of this server. The MDF size is rather substantial at 420GB. The log size is inconsequential for the purposes of this task.

Here’s the interesting part. Take a look at the current file system size versus the internal fill size. Record the internal fill size, as that’s what we’ll be using to help with some math shortly.

Now, how many files do you need? Here’s my standard DBA response—it depends. For the purposes of this test, I’m going to add seven NDF data files to complement the primary MDF. Your mileage may vary based on your workload.

How large do these files need to be? Take the internal fill size on the MDF, divide by the number of data files you want in total and round up to the nearest megabyte. If the database is active with a lot of data being added, you might want to add a bit more just to have it balance by the time we’re done with this task.

SELECT f.name AS [File Name] , f.physical_name AS [Physical Name],

CAST((f.size/128.0) AS DECIMAL(15,2)) AS [Total Size in MB],

CAST(f.size/128.0 – CAST(FILEPROPERTY(f.name, ‘SpaceUsed’) AS int)/128.0 AS DECIMAL(15,2))

AS [Available Space In MB], f.[file_id], fg.name AS [Filegroup Name],

f.is_percent_growth, f.growth, fg.is_default, fg.is_read_only,

fg.is_autogrow_all_files

FROM sys.database_files AS f WITH (NOLOCK)

LEFT OUTER JOIN sys.filegroups AS fg WITH (NOLOCK)

ON f.data_space_id = fg.data_space_id

ORDER BY f.[file_id] OPTION (RECOMPILE);

Now is the time to determine if these should be placed on the same disk or if they should be distributed across more disks. I’m doing that on this server to leverage the disk controller queues to more widely distribute the storage activity and see better overall performance when under pressure. I’ve attached three more virtual disks to this virtual machine, and the four are spread on the four disk controllers on this virtual machine. All disks are formatted with a 64KB NTFS allocation unit size with the large FRS flag enabled. Let’s place two of these files on each disk with the fourth holding the last NDF with the MDF.

Here’s a trick: I set the maximum file size of each of the new NDF files to be the percentage of the current main file space consumed.

Now, we’re going to use a little-known command to empty the MDF file. It’ll drain the file completely, but since we capped the file growth of the NDF files that we attached to limit their growth rate, this command will run until we have filled the NDFs, then fail. It will take longer to perform this operation, but it keeps the database online while it runs. You might have a bit of a performance hit from the CPU and I/O impact of this running process, so it’s important to think about timing when running this operation.

You can watch the process work with the internal used space query listed above; the primary MDF is draining while the other NDF files are slowly filling up.

Again, it takes time for this process to finish. When it finally ‘completes’, the EMPTYFILE command will fail due to maximum file size limit on the NDF files.

FYI—Index optimization routines can cause a circular block with this process that I have encountered twice while running this process, so keep an eye out if you see this occur.

Now, your internal data consumed space rates are almost identical.

Verify the autogrow rates are now the same between the data files. Remove the file growth limit on the NDF files.

Perform a one-time shrink of the primary MDF file to shrink it down to where it is the same size as the others.

It will most likely be slightly out of balance. SQL Server does a pretty good job with the round robin algorithm for internal file fill rates, and it will finish balancing and then round robin filling internally as you continue to add data through normal usage. If you need to increase the size on some of the files so they match, go for it, and SQL Server will fill accordingly so it finally balances.

You might also check if you need to enable autogrow all files at the same rate. This could mean that the database users might need to be punted from the database to enable the change. Do this during a maintenance window.

Sample your SQL Server disk stall rates and see what different you experience once this goes live.

I hope this helps you improve the operational efficiency of your SQL Server database data files, and you get better performance as a result. Let me know how this works for you!

Update: If you encounter an error like the following, just shrink the main MDF file down and repeat the emptyfile operation.

February 25, 2022

Akamai: Buying Linode | Firefox: Not OK | Gone: Google Vaccine Mandate

Welcome to The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: Linode gets bought by Akamai, Firefox market share is “measly,” and Google brings staff back to the office.

1. Akamai + Aker = ‘Synergy’

First up this week: Why is Akamai buying Linode? Whatever the reason, it’s a big payday for its solitary shareholder: Not far off a billion dollars.

Analysis: There goes the neighborhood?

The 100 lb gorilla of edge computing and CDNs is promising not to mess with Linode’s winning open source cloud formula: No change, steady as she goes, etcetera. But how many times have we heard that before?

Here’s local scribbler Paige Gross: Linode’s $900M acquisition by Akamai is a ‘game changer’

A household name in the Philly tech scene … CEO Christopher Aker founded the company in 2003, and it’s been bootstrapped ever since, growing to about 250 employees. … Aker has owned 100% of Linode since he founded it.
…
Aker said the deal brings the company closer to solving evolving challenges “as cloud services become all-encompassing, including compute, storage, security and delivery from core to edge. … We’ve been talking about ‘alternative cloud’ — alternative to the big guy — and now we’ve sort of validated ourself in this market.”
…
The Old City company maintains “well over a million accounts” but has anywhere around 150,000 active users of its platform at any particular time. Linode’s HQ, the bank building at Third and Arch Streets, remains. … For clients and Linode employees, there won’t be too much noticeable change [Linode] says.

Why does Akamai want Linode? Jonathan Greig asked the CEO:

Akamai CEO Tom Leighton [explained] that Linode has great customer support and is already in 11 locations, which Akamai is going to “dramatically” expand. … Leighton also noted the September 2021 acquisition of Israel-based Guardicore, a cybersecurity company that offers a micro-segmentation solution to reduce the potential attack surface of corporate networks, secure applications, and meet compliance standards.
…
According to Leighton, the company is expecting the cloud compute category — which includes edge applications, its net storage business, and Linode — to reach “well over half a billion dollars in 2023. … We were pioneers in edge computing and now we’re taking a big step forward in cloud computing with Linode.”

But here’s a worried-sounding zoid.com:

Well good for them but I hope [Akamai] don’t screw it up. Linode is a great hosting company.

2. Firefox isn’t OK

Last week, a journalist innocently asked, “Is Firefox OK?” And people lost their minds.

Analysis: No, not OK—it’s a big problem for DevOps and the web.

We need Firefox and Gecko. A Chromium monoculture is bad for the web and bad for DevOps. (Before you ask: No, the existence of WebKit doesn’t change things, thanks to Apple’s ridiculous policies). Much as I tried to say something nice about Firefox last month, its market share is, frankly, pathetic.

Matt Burgess: Is Firefox OK?

In the two decades since Firefox launched from the shadows of Netscape … the browser has slid to less than 4 percent of the market—on mobile it’s a measly half a percent. … Its fate also has larger implications for the web as a whole.
…
Each year Google pays Mozilla hundreds of millions of dollars in royalties. … In its 2020 financial results … Mozilla listed its total revenue as $496 million. … The Google-Mozilla deal was last renewed in 2020 and is expected to expire in 2023. … Mozilla and Firefox acknowledge that for its long-term future it needs to diversify the ways it makes money.
…
Firefox still matters: … The browser market is dominated by Google’s Chromium codebase and its underlying browser engine, Blink. … Microsoft’s Edge Browser, Brave, Vivaldi, and Opera all use adapted versions of Chromium. Apple [has] its WebKit browser engine [but] other than that, Firefox’s Gecko browser engine is the only alternative.

Firefox, how do we love thee? Let not_count_zero count the ways:

I still use Firefox because:
a) I remember Internet Explorer and the standards wars. …
b) I don’t trust Google. …
c) Most sites work well.
…
I do have questions though. … They’re currently getting around a half a billion‽ What are they doing with it? … This seems really off—really, really off.

But heed a deeply worried Thom Holwerda:

The decline and potential demise of Firefox is a massive problem that everybody seems to be kind of tiptoeing around—too afraid to acknowledge that if Firefox were indeed to disappear, we’d be royally screwed. We’d end up right back where we started 20 years ago, with Chrome being the new IE6.
…
The situation is especially dire for … Linux users, developers, and distribution makers. … Gnome Browser or KDE’s Falkon can barely be taken seriously, and … are based on Apple’s WebKit, which isn’t a great position to be in.

3. Google’s Return to Work Plan Drops Vaccine Mandate

Google is planning “celebrations” to welcome back employees after being fully remote. And in practice—unlike at IBM—this doesn’t mean a vaccine mandate.

Analysis: Vocal minority wins—or do they?

It was just three months ago that Google said it “firmly stands behind our vaccination policy.” What changed? It’s unlikely to have been due to a tiny minority of staff publishing a manifesto.

Jennifer Elias: Google relaxes mandates

The company will no longer require vaccination as a condition of employment … as it prepares to bring workers back to the office … at least three days a week for a “hybrid” work model. … The company [had previously] told employees that they must comply with vaccine policies or they’d face loss of pay and eventually loss of employment.
…
According to Google spokesperson Lora Lee Erickson … the company dropped the requirement … after removing the Jan. 18 deadline it had set for employees to either get vaccinated or get exemption approval. She declined to provide further details on the policy or the reasons for the reversal.
…
Google Real Estate and Workplace Services VP David Radcliffe [said Google] is preparing to begin its 30-day transition period to the hybrid work week if conditions continue to improve. He said his team is planning “celebrations” to welcome back employees. … Unvaccinated employees who are approved to enter offices will still need to follow additional protocols, including testing and wearing a mask.

It’s too simplistic to say the anti-mandate brigade are also anti-vaxxers. For example, raxxorrax:

I am vaccinated and HR knows this. … But if they officially demanded a certificate, I think I would have called it quits. Many people don’t have that option [but] there are consequences for such unreasonable demands.
…
I understand a mandate for vaccinations in certain occupations relating to health. It is something you have to personally accept if you want to work in the field.

Although a few others are way over at the end of the bell curve. Greg Jinkerson:

Don’t get excited, [Google is] still evil and stupid. … Now they’re backing down for some reason, [but] this is barely anything notable as far as a rollback of restrictions. [It] is not any kind of encouraging news.

The Moral of the Story: Failure is the foundation of success—and the means by which it is achieved.

You have been reading The Long View by Richi Jennings. You can contact him at @RiCHi or tlv@richi.uk.

Image: Aleksey Kuprikov (via Unsplash; leveled and cropped)

February 24, 2022
Merging Secrets Management and Configuration

Fresh from picking up $5.25 million in funding, CloudTruth CEO Greg Arnette talks with Mike Vizard on this episode of the View With Vizard about why configuration and secrets management need to converge. The video is below, followed by a transcript of the conversation.

Announcer: This is Digital Anarchist.

Mike Vizard: Thanks for the throw. We’re here with Greg Arnette, who’s the CEO for CloudTruth, they just raised $5.25 million to help us with these configuration issues that seem to plague us. Greg, welcome to the show.

Greg Arnette: Thank you. It’s great to be here, and thanks for the opportunity to tell your audience about CloudTruth.

Mike Vizard: So, what is the configuration problem, and why does it not seem to wanna go away? It’s been around for a while, things appear to be getting worse, and what’s to be done about it?

Greg Arnette: Exactly. So, that ties into the history of founding this company. Both myself and my Co-founder were prior CTOs and DevOps leaders for several cloud-based SaaS companies, and we saw that our DevOps teams were continuing to build internal tools to address issues around configuration sprawl and complexity. And these tools tend to be the weak links in terms of solid deployments, good up time, good security, and basically, slows teams down.

So, the history of kind configuration sprawl and what we see as the challenges is sort of driven by a number of macro trends—first, the fast rise of Kubernetes; everyone wants to get on the Kubernetes bandwagon. That introduces new complexities around configuration management, new sets of tools that haven’t been sort of well adopted inside of DevOps shops. Another trend is the breakup of monoliths to microservices adds lots of new dimensions on configuration complexity. And then there are the traditional needs around provisioning infrastructure, configuring your apps, and managing secrets are the sort of legacy challenges around configuration management. And as the cloud gets more mature and with more capabilities, configuration is not getting easier, but getting more difficult.

So, CloudTruth is here to address those concerns. We heard, during our product market fit research where I interviewed over 500 cloud and DevOps leaders on their challenges managing configuration, that this over reliance upon tribal knowledge in terms of how a system is configured and why it’s configured a certain way is just held in key team members’ heads, and that’s not a very durable strategy for going forward or for on boarding new folks. So, there’s an element of CloudTruth that provides collaboration and sharing around configuration settings and context to help reduce that need of, or that sort of burden of the cognitive load to keep track of how are things configured, where is the data, how can I change it, what changed recently—that type of thing.

Mike Vizard: You guys also acquired a company in this process in the secrets management space, so where does configuration and secrets management converge and how do we think about that?

Greg Arnette: That’s a great question. So, we acquired Tuono, we’re thrilled to bring in the Tuono team, including Jesse St. Laurent, who was the CTO, who joins us as our Chief Product Officer. Jim King, Mike Healey, Mike Stack all joined us, they were the founding engineers at Tuono.

And what we did was, we took the Tuono secret management engine, which was cloud native and we’ve now included that in the CloudTruth platform which rounds out our offering. So, CloudTruth, while it is also a configuration data hub to synchronize your configuration settings from all these multiple tools is also itself a parameter store and secret store that customers can use if they don’t already have existing parameter stores or secret stores in their environment.

Mike Vizard: And in that context, what does cloud native mean? Because some will people say, you know, it runs in the cloud; other people will say that it only runs on Kubernetes, it’s optimized for microservices and containers. Or is there some middle ground there and what do we think about cloud native—what context are we using that phrase?

Greg Arnette: Yeah, when we use cloud native, we mean or refer to the capabilities that are provided as part of core services at Amazon, Azure, and Google. So, an example is, Amazon themselves provide a parameter store, they call it AWS Parameter Store. Google and Azure provide the same kind of internal capabilities. Customers can also bring their own parameter store, like run something like Console on top of the cloud or using Vault sometimes as a general-purpose parameter store.

So, the cloud native offerings like AWS Parameter Store, Secret Manager, and the equivalent on the other clouds are things that customers can use, they have different price points. We provide a layer of management and visibility and observability to all that config data stored inside of all these different systems.

Mike Vizard: And when you talk about unifying configuration, are we replacing Terraform and CloudFormation, or are we just finding some way to layer some form of abstraction around them that makes the whole process easier to manage? Walk me through that a little bit.

Greg Arnette: Yeah, you know, we’re not replacing Terraform or CloudFormation. We’re designed to coexist with the customers’ existing investments and their configuration tooling. So, whether it’s provisioning tools like Terraform, CloudFormation, Pulumi, or app config tools like Ansible, Puppet, Chef, Saltstack, or secret tools like Vault or the cloud native versions of those capabilities. We coexist and become a metadata wrapper around those different tools.

Now, if customers don’t have some of those capabilities, we have functionality in our platform that can fill the gap, but more and more customers already have these systems in place. They’re not looking to rip everything out and replace it, but they’re looking to address these issues around configuration sprawl that leads to a misconfiguration causing unplanned down time or a security incident.

Mike Vizard: We have been talking about DevOps and DevSecOps forever, and the idea has always been that we’re shifting more responsibility for the IT environment to the left of the developer. Sometimes they like that, sometimes they don’t.

But I wonder, are we not approaching some sort of concern or maybe a backlash where folks are saying, “Hey, you know what? This isn’t really working. We have all this misconfiguration out there, we’re maybe running faster, but things are less secure, and we have more risk than ever.” So, is there a balance to be struck, or what’s your sense of where are we on this journey?

Greg Arnette: That’s a very interesting question. This is something that we hear all the time in our outreach to our customer audience is what their journey looks like for adopting shift left or GitOps types of operating principles. We’ve seen a number of patterns emerge over our hundreds of interviews. Specifically, most teams do want to give developers more capabilities to do things themselves and reduce that burden on the Ops team, but they still want Ops or DevOps teams to have the overall sort of judgment and enforce the guardrails that were put in place by the security and compliance teams and by the other teams that are sort of deciding what are the best practices.

So, with CloudTruth, we’re kinda serving both audiences in a purposeful way. You have centralized control and visibility that DevOps wants. They wanna build and enforce lockdowns, enforce default settings that can only be overridden with a permission or an override that’s allowed as part of a workflow. But you also provide capabilities for core developers to manage the config for their own environments and to suggest configuration changes that then can be adopted more system wide.

So, we’re serving that duality that exists today. We’re gonna let the customer decide on where they ultimately land about developing shift left principles and moving that direction. But we see a lot of interest in that, and it helps to reduce that—you know, again, that cognitive load and that context switching on the DevOps professionals. Because so many times, they’re being bothered by other folks and other developer teams, like, “What’s the setting for this Redis cluster? Why is our Mongo configured this way? How do I tune my elastic search test cluster to match production?”

That information will all be self-serviceable and findable inside the CloudTruth platform. And our role based access control permissioning system allows view only, read only, read/write access to the appropriate areas, and then DevOps teams can sort of wall off the production systems from other people having chances of changing those settings.

Mike Vizard: Mm-hmm. What is the role of the security team as we go forward? It feels like, if we shift everything left to the developers, what are those guys doing?

Greg Arnette: They still need to be involved in terms of ensuring that no bad information gets in and no good information gets out. So, we provide a number of views into configuration data that are helpful to security teams. First is, what changed most recently in terms of your compliance management reports for SOC 2 and other requirements and keeping track of changes. That’s really hard in a dynamic environment, especially cloud-based where you have microservices firing left and right, coming up and down. The old traditional CMDBs that were popular in the on prem world don’t really fit well in the new way that we’re using the cloud.

And so, CloudTruth is a self-documenting change management control system that is, behind the scenes, keeping track of all the version settings of every configuration value that we’re monitoring, and then we provide views into that data that can be consumed by the security or compliance teams to get better insights for their needs without having to bother the DevOps teams.

Mike Vizard: Do you feel like the bad people, otherwise known as cyber criminals, are getting better at scanning for misconfigurations and looking for these vulnerabilities to exploit? And we hear a lot about software supply chains these days—it seems like, in a lot of cases, the root cause of the problem is just misconfigurations.

Greg Arnette: It’s true. We’ve found, in our own research, that 75 percent of unplanned down time or security incident was caused by a misconfiguration when you ultimately read the root cause analysis and do all the internal tracing.

So, what we wanna provide are the best practices as early as possible in the software development life cycle process to implement good config hygiene. And then secondary to that is, once config is out there in the wild, provide monitoring and insight into how it could affect security vulnerabilities or security posture. Since everything these days is defined as infrastructure as code, it’s all about analyzing all the different locations where config values are stored, making sure those are secure and locked down, and then being able to use any kind of pattern recognition to understand where certain areas can be vulnerable to being taken advantage of by the nefarious factors out there in the world.

Mike Vizard: Do you think we’ll get to the point where we can use automation to kinda get ourselves out of this mess? We have APIs and CLIs and everything else that’s out there—shouldn’t we, at some point, have enough intelligence in the work flows to say, “Hey, this thing you’re about to deploy is misconfigured, so don’t do it”?

Greg Arnette: That’s part of our goals down the road is, we have a very thoughtful strategy how we wanna launch CloudTruth as a full configuration data management platform. So, the first goal is to get inserted into a company’s work flows where we have access to the data and can provide value with reports and work flows. The second goal is then, once we’re now managing this data on behalf of the customer, to apply AI and ML, looking for patterns, recommending optimizations, best practices, vetting what we see from a customer perspective against best practices being published by other standards bodies that are looking at this from different perspectives.

One goal of CloudTruth is to be that configuration data layer management system that we think most companies using the cloud need these days.

Mike Vizard: We also hear a lot about artificial intelligence—will that get applied to this space? Is there any scenario where we’ll just have a bunch of machine learning algorithms running around, figuring out what’s going on?

Greg Arnette: We firmly believe that that is definitely gonna be happening a few years down the road. I think the maturity model is just getting started. The first act in getting that up and running is getting access to the data for trending the models and analyzing the trending results, optimizing the model. So, a full observe-orientate-decide-act OODA loop is involved here in terms of making sure those models are accurate, but we think that’s gonna be a big benefit in what we can provide down the road.

Mike Vizard: So, what’s your best advice to folks? What should they be focusing on today to get to that nirvana tomorrow? Is there same way I should be organized, is there some way I should be talking to my developers? What do you think?

Greg Arnette: There’s a couple themes that come to mind. The first is—which sounds almost obvious these days—is make sure you are able to do infrastructure as code ideas at all levels that you can, and that’s tied into automation. So, it’s a big portion to continuous deployment, CI/CD pipelines. Once you start the development of those types of workflows that accelerate getting what developers are creating out in front of the customers, whether it’s an internal app or external SaaS or mobile app, accelerating that team velocity is really a key element in terms of making that possible.

The other area is this notion that you wanna implement systems that reduce the amount of copy and paste. So, that’s what we call the Do Not Repeat Yourself, the DRY approach to infrastructure as code management. So, that’s a key theme behind CloudTruth is, we provide capabilities that let you manage your multiple environments with the faults, inheritances, and overrides from a centralized capability, but still allow flexibility in your environment tree to manage certain sub-environments in different ways as needed.

So, different developers can have their own custom environment, but they’re gonna inherit default values that are sanctioned by the architecture team or the security team. And then the overrides have to be allowed by a permission basis.

So, there’s a couple sort of themes that are coming together as we go through 2021 around automation, infrastructure as code, shift left, and the DRY approach to managing input values to all the IAC tools.

Mike Vizard: Hey, Greg, thanks for being on the show.

Greg Arnette: Thank you very much. Have a great day.

Mike Vizard: Alright, awesome. Hey, guys, we learned a lot about security there and things we didn’t know and—hey, there’s hope for the future. Back to you guys in the studio.

[End of Audio]

February 21, 2022
Natural Language Query (NLQ) is Key for Self-Service BI

Modern business intelligence (BI) and analytics software solutions offer more ways to explore data and find insights than ever before. However, ensuring everyone in the enterprise can use analytics independently, when they need it, remains a challenge.

For analytics to be adopted across the full enterprise, your tools need to be tailored for all users.

While many BI solutions today provide streamlined experiences, some data literacy and knowledge is required to fully understand them. Dashboards, for instance, are considered self-service BI tools, but they are often still too technical for the average person to use effectively.

Today, only two out of five (40%) organizations report their people can analyze data without getting help from IT, according to Ventana Research. To better enable business users to interrogate their data independently, certain BI vendors now provide a natural language query (NLQ) capability that sits alongside their dashboards and reporting. Rather than having to search for answers in a traditional dashboard or chart, NLQ allows analytics users to ask questions of their data directly.

An Overview of NLQ

Natural language query is a self-service BI tool that provides the ability for an analytics user to ask a question using non-technical language and get an automatically generated answer instantly. Using data modeling and machine learning technologies to parse questions for key terms, NLQ scans related databases and generates a tailored report or chart that provides relevant insight.

The integration and implementation of natural language query capability, as well as the complexity of the questions and the types of data supported, varies between vendors. The most common and traditional approach is search-based NLQ, which places a free text search bar somewhere within the user interface (typically on a dashboard) that allows BI users to begin typing a question and get a list of reports and charts generated quickly as potential answers.

A smaller number of vendors also include support for voice commands in their NLQ solution.

As NLQ increasingly becomes a part of BI ecosystems, however, some vendors have evolved their natural language offering to account for additional barriers: A user still has to know what question to ask, and how they can use it to avoid inaccurate or irrelevant results to their question.

The new approach is called guided natural language query, or guided NLQ, which takes the concept of NLQ further by programming the solution itself to guide the user as they type a question, helping them structure it using pre-defined sequences and suggested prompts.

This eliminates the burden of knowledge or any potential problems in accurately interpreting the semantics (language) of a user’s question, as the system itself assists them in building it, from start to finish. They don’t need prior technical knowledge or need to go to IT to get started finding answers from data.

When employed correctly, guided NLQ can help make the use of analytics more pervasive and open up analytics for every type of business person in the enterprise—not just experts.

Self-Service That Suits Every Enterprise User

The aim of NLQ is to help workers not accustomed to traditional, structured BI tools find insights and information they need to inform and make business decisions, while also being a helpful tool for advanced users throughout the enterprise.

For non-technical analytics users, NLQ is an easy way to get detailed answers from their data faster than exploring a dashboard or chart and use it as a springboard for their ad-hoc reporting.

Similarly, advanced users can leverage NLQ, whether guided or traditional, to quickly generate a report or chart and further build upon it.

Generated insights using NLQ can be added into existing analytic content, such as dashboards, reports and data stories, to enhance them with additional detail, relatively quickly and easily.

Finally, NLQ can be embedded into the interfaces of your users’ workplace applications, to make analytics far more ubiquitous in their day-to-day workflows. They can ask a question, get an answer, and start exploring data much faster and more easily than via dashboards alone.

Ultimately, having an awareness of your users’ varying self-service BI needs, and how the new wave of tools such as Guided NLQ can help to further open up analytics to more people, will help you ensure your analytics tools are adopted and usable by everyone throughout the enterprise.

February 21, 2022
Automation is Key for Success of 5G at Scale

5G is more than a progressive step; it is a catalyst for individuals, society and industries to meet their digital aspirations. 5G goes beyond connectivity by providing a platform to collaborate across industries, and 5G networks will be at the center of an ecosystem that pushes society’s continued digital transformation forward. By design, 5G networks will be flexible and modular, with technologies such as network slicing, software-defined networks (SDN), cloud-native and cloud radio access networks (cloud RAN). A flexible architecture makes it feasible to increase overall network capacity as needed, completing the standardization of application programming interfaces (APIs) towards underlying infrastructure, which will be key for automated connectivity to a heterogeneous network. APIs have sparked a revolution in banking, finance, health care and other fields, and now it is communications’ turn.

Communications service providers (CSPs) can’t lose sight of the imminent innovation coming from cloud and cloud-native software. 5G is where telco meets IT. Virtualization, cloud edges and containerized 5G deployment alongside a legacy network bring tremendous challenges with numerous interfaces, processes and complexities. The basic automation model that exists today will not be able to support the next-generation networks that come with a plethora of connected devices and the volume of traffic that must pass through. End-to-end, closed loop automation is going to be the catalyst that accelerates the space from network-centric operations toward customer-centric operations.

Why Automation is Crucial in 5G

5G drives incident-driven operations toward data-driven operations. It also drives human-triggered automation toward outcomes, triggers processes and initiates massive machine-to-machine communications. At the same time, the internet of things (IoT) has vastly increased the number of endpoints that need to be managed and, as network slicing comes to fruition, network slices will include SLA delivery models, which will be beyond humans’ ability to manage.

As a result, CSPs must rethink the way their networks operate now and enhance their existing value-adds by complementing their existing, strong cellular expertise with software capabilities. As organizations integrate their networks with cloud assets, databases and application assets, they must focus on incorporating automation at every step to efficiently manage their 5G networks and enable new 5G offerings.

AI/ML and Automation

5G is evolving alongside AI and ML. The high speed and low latency of 5G along with AI and IoT are going to significantly impact the way we live and work. 5G and intelligent connectivity enable automation to go through a complete transformation from digitization to artificialization. ML is pushing CSPs from playing the role of digital service provider to becoming cognitive service providers. AI will augment human decision-making in telecommunications to achieve newer use cases. The power of AI can be used to identify features and qualities in the current environment from a large set of big data, then analyze the use cases and predict future network failures which will help to mitigate the impact of any possible failure.

Enabling digital innovation is a high priority for CSPs as they transition from a prescriptive model to a declarative, API-driven and DevOps model. Success will ultimately depend on efforts to build the necessary organizational readiness. By leveraging cloud technology, managing risk, embracing openness and establishing a human-augmented AI model, CSPs can break silos in their network and enable this transition to happen.

Are CSPs Ready to Embrace the New Era of Automation?

In the 5G era, mobile will become even more central to our daily routines. According to a GSMA report, the economic value created by 5G connectivity will reach $1.4 billion by 2025 and 5G will contribute $2.2 trillion to the global economy over next 15 years.

5G networks will require automation that can support multi-domain and multi-vendor technologies, as services such as network slicing will traverse across multiple network segments like radio, access, core and edge, which may contain a mix of virtual and physical network functions.

On their journeys from communications service provider to cognitive service provider, many network operators today have orchestrated network and IT domains, but few have the capability to orchestrate end-to-end services, given the fact that physical legacy networks will coexist with cloud-native network functions. While network slicing and tailored connectivity are still in their early days, full automation will not happen without end-to-end service orchestration.

To enable automation on every aspect of the network, CSPs must embrace fully interoperable, data-centric solutions that offer the visibility and monitoring that is expected of cloud-based applications. By working closely with customers, each network function can be built in microservices with fully automated testing and regression testing and by leveraging DevOps for carriers.
5G is the catalyst that is converging telecom network engineering and operations with IT. The vast amount of data to be analyzed for insight-driven business models is forcing a cultural shift from pure network management to services management. Evolved, smarter networks, new agile and insight-driven business models all require that 5G automation be taken to the next level. Simply put, automation is not an option but a necessity.

February 21, 2022
Netlify Leverages GraphQL to Simplify Access to Backend Services

Netlify this week added a Netlify Graph tool to its portfolio that makes backend services available to developers via a single click. The tool aims to simplify DevOps teams’ access to those services when building their applications.

Netlify Graph is based on the GraphQL query language for application programming interfaces (APIs) and enables developers to integrate services such as GitHub, Salesforce and Stripe within frontend and web application development tools without any direct intervention required from a DevOps team.

Netlify provides an application development framework based on JavaScript, application programming interfaces (APIs) and markup languages, otherwise known as a JAMstack, to isolate frontend and backend components of an application.

Netlify CEO Matt Biilmann said Netlify Graph is based on the GraphQL technology the company gained when it acquired OneGraph. The overall goal is to make it simple for frontend developers to invoke backend services accessed via either GraphQL or REST APIs, he said. Services based on GraphQL can be especially complex for developers to invoke as they navigate the management of tokens and application secrets, Biilmann added.

It’s not clear to what degree GraphQL APIs will supplant REST APIs. However, developers tend to prefer GraphQL APIs because they provide more granular control over what data is accessed. The challenge is the number of backend services that expose GraphQL APIs is still comparatively limited. As GraphQL becomes more widely adopted, the level of effort DevOps teams now need to expend to expose backend services should decline as tools such as Netlify Graph are employed by frontend developers.

As a result, at least theoretically, the rate at which new applications are built and deployed to drive digital business transformation initiatives should increase. Most IT teams will not be replacing REST APIs with GraphQL-based APIs overnight, but the percentage of new applications that rely on GraphQL APIs will steadily increase. DevOps teams looking for easier ways to provide developers with simpler access to backend services now have an incentive to embrace GraphQL.

Ultimately, Biilmann said, the goal is to enable developers to build applications without having to directly engage anyone on the IT team. Each backend service can be managed in isolation from the frontend of any application. It’s not clear how long it might take to achieve that goal, but as responsibility for the end-to-end management of the application experience continues to shift left toward developers, the need to surface backend systems-as-a-service becomes more pronounced. In fact, given the current focus on improving developer productivity, IT organizations might soon face a mandate to embrace GraphQL more broadly. After all, every minute that a developer spends on plumbing is time they’re not spending writing actual business logic.

Naturally, it may take time for enterprise IT to be truly transformed into a set of services that developers can easily consume. But as progress continues to be made, that dream may finally be realized.

February 18, 2022
Agile and DevOps for Kiosks

Alan Shimel talks with Sam Zietz, the CEO of Grubbrr and Touchsuite, about how software for kiosks can use Agile and DevOps to keep up with a wide range of hardware profiles. The video is below followed by a transcript of the conversation.

Announcer: This is Digital Anarchist.

Alan Shimel: Hey, everyone. Welcome to another segment here on TechStrong TV. I’m really happy to be joined by a good friend of mine today. His name is Sam Zietz. Sam is the founder, CEO of GRUBBRR. You may not know the company but Sam’s going to tell you all about it. Hey, Sam. Welcome to TechStrong TV.

Sam Zietz: Al, thank you for having me on. Excited to see you again.

Alan Shimel: Yeah, it’s been – well, with COVID it’s been a long, strange trip. Sam, we’ve never had you on TechStrong TV though. We’ve never really talked about the company. Why don’t we start with that. Give people a little background on GRUBBRR and maybe a little of your own background.

Sam Zietz: Sure. So GRUBBRR is the leader in self-ordering technology. When you talk about self-ordering technology you think kiosks, mobile ordering, online ordering. And in reality, this was going to naturally occur over the next 5, 15 years. That’s before COVID hit. COVID came about and acted as a huge accelerant. So if you think about how we used to go to a bank and there used to be a teller, that teller got replaced over a 5 to 15-year period of time by online banking and ATMs.

We used to go to the airport, and in the airport we used to see a ticketing agent. That ticketing agent got replaced by a bank of kiosks or QR codes on your smart phone. Same thing was going to happen in many verticals like restaurants and hospitality and retail, and it’s going to be a combination of kiosk, mobile and online, and that online will be the company’s website or a third party delivery service like an Uber Eats, a Grubhub, or a Postmates. What ended up happening through is COVID, and now all of a sudden nobody wanted to interact with a cashier and cashiers didn’t want to interact with consumers either.

This was all of a sudden a hazardous position and people didn’t want to shop any longer for that type of work. So that accelerated the move towards self-ordering technology. Then Joe Biden was elected president, and one of this four pillars was this $15.00 an hour minimum wage, and regardless of where you fall out politically, whether you think it will be successful or not, he has, and whether it’s passed or not the minimum wage has increased. And right now we’re in a labor shortage on that end of the market for a combination of factors, many of which is people don’t want to come back and do those types of jobs.

And as a result, you’re seeing especially in restaurants that they can’t even open their doors many times because they don’t have the employees. So for all of these reasons we’ve accelerated the movement towards self-ordering technology.

Alan Shimel: Yeah. I mean, Sam, this all falls under what we call digital transformation, right? And digital transformation, as you mentioned, was well underway before COVID, but we’ve probably accelerated four to seven years of digital transformation in the last year, year and a half. And the move towards automation, which is what this is, was again well under way. Quite frankly, when we look at should we automate everything – this is a question for academics – should we automate everything, should we automate only what should be automated or should we not automate everything for the sake of preserving jobs, and whether you believe in a Star Trek future where you get a basic, whatever they call it, wage where they send you money or not, quite frankly, if a machine can do it better they don’t take sick days, they don’t steal, purposely anyway.

Hopefully not. They’re a better employee in some regards. So if there’s a machine that can do the job better, a futurist or technologist will say by all means the machine should do the job then because that frees up people to do hopefully higher-level work, more valuable work. Now are there some people that can’t do higher level, more valuable work and what do we do with them as a society – that’s probably a discussion for another day. But the fact is that today we have the technology, to quote an old TV show, to do this, and that’s really what you guys are doing there at GRUBBRR.

Sam Zietz: Yeah. And historically this should’ve occurred years ago. It really was restaurant owners said, “Hey, you know what? We’ve been doing it the same way for the last 20 years,” and because labor was so cheap and because the minimum wage was so low, instead of investing in technology like almost every other industry has they said, “You know what? Let’s just throw cheap labor at it,” and that’s what occurred. COVID has exposed those businesses that had not invested in technology, and quite frankly rewarded those companies that had been proactive.

They were extremely successful during the pandemic, the ones that had digital, they had an online presence, they had these self-ordering applications already in place. They were hitting record numbers. Everybody else either exposed or permanently shut down as a result. And by the way, these aren’t jobs that anybody wants.

Even pre pandemic, the average turnover for a cashier in this country was 150 percent annually. I think Panera put out a stat before COVID that they were at 100 percent. And they were bragging that they were at 100 percent. So they were proud of the fact that every one of their employees –

Alan Shimel: It was only 100 percent.

Sam Zietz: Yeah. So these aren’t –

Alan Shimel: There’s no doubt. Look, I think we’re both saying the same thing. This is the way it was going. We just had an accelerant take place. So let’s talk now about GRUBBRR. So you guys are filling that void by developing software solutions that allow for self-ordering. And whether people are ordering online via the internet for like a third-party delivery or in person, it’s still a software-empowered transaction. Like everything else, software is leading the world.

In your case though, Sam, the challenge is that even with self-ordering it comes in a lot of form factors. It comes in a lot of shapes and sizes. And how do you make a software that is shape and size, form-factor independent? I imagine that’s got to be a challenge.

Sam Zietz: Yeah. Well, we’ve got talented dev people, so from my perspective it’s easy. They do all the hard stuff.

Alan Shimel: You didn’t write too many lines of code. I get it. But the challenge is there.

Sam Zietz: We’re agnostic on the hardware side, so we work with all of the leading kiosk manufacturers too. They bring us in for the software. Why? Because nobody’s going to buy a kiosk by itself. A kiosk by itself doesn’t do anything. It’s the software that does it. Just like your Dell computer doesn’t do anything.

It’s the Microsoft and the other applications that you put on it, that’s the reason you’re buying the computer. So it works the same way on the kiosk. We’re agnostic. So it’s funny, we built this beautiful restaurant of the future in our headquarters here that people can come in and they can see everything in a working environment, but then after they realize we want a kiosk or we want KDS or we want mobile, whatever it is, we take them next door into our showroom and there we have everything.

In there they can decide do we want a wall mount, do we want a tabletop, do we want freestanding, do we want a 15-inch, a 21-inch, a 24-inch, a 32 – you know, whatever they want. Do we want it in a portable fashion where it’s truly mobile? All of those options are there, but the software at the end of the day, the core that’s running it, it’s the same. It’s the same software. And you’re right, that’s exactly what we spent our time building, was software regardless of form factor that will work the same.

And the key to this is that somebody can operate it with no training. So you don’t need to – our competitors in the kiosk space, for the most part, fall into two categories. There are POS companies that turn their POS system sideways and say now it’s a kiosk. Well, that doesn’t work. Or they’re writing an app on an iPad, and that clearly doesn’t work either. So really the advantage in which you were talking about online and now going in store with a kiosk, one of the great things about that is the marketing team and the brand owners can now curate that user experience much like they do with the online experience.

So you can control and provide that consumer the absolute best experience, where before you had a cashier and maybe you taught them at the end to say, hey, at the burger place, do you want fries with that? Okay, and more people buy fries because the cashier asked them if they wanted fries. However, if I’m ordering a salad the likelihood that I’m going to buy fries is pretty low. However, I might take a fruit cup, I might take a healthy treat.

So being able to, again, pair offerings to the items that that consumer would like increases the average ticket and improves the experience for that consumer. You also eliminate all the errors, right? Because now you’re putting it in yourself. How many times have you gone and said, “Listen, I’d like a hamburger – I’ll have a cheeseburger with extra ketchup, no pickles,” so they go, “Got, it extra pickles, no ketchup.” You’re like, no.

So there’s a whole host of reasons why that experience is better and could be faster, because maybe you could only afford to put one cashier in there, but you could put a whole slew of kiosks in there for a fraction of the price of one cashier. Well now you eliminate wait times and you can redeploy personnel into the actual prep of food and improving consumer experience.

Alan Shimel: Yep. There’s another issue I wanted you to touch on, Sam, and that is really one of the inherent advantages of modern software and whether it’s an app, think of it as an app, or it’s just portable software that’s not particularly tied to – hardwired, if you will, into the form factor of hardware, the ability to update on the fly. Right? You change your menu items, you change your price, your running specials, or I mean really, really big functionality – we’re going to start accepting PayPal or Apple Pay or Google Pay or whatever the – we’re going to start taking bitcoin.

I don’t care how you want to pay for it. But right? We need to update that. By having it all dependent on software, not burned into the silicon, we do that as well. How does GRUBBRR handle that? Like the whole update process?

Sam Zietz: Yeah. So first off, we can update everything in real time as well as – so we can also be notified before even the client knows that there’s an issue with software. So maybe their internet went down because their provider – there was a problem, whatever. Many times we’re calling them and saying, “Hey, your internet’s out.” Oh, wow. Somebody was in the closet and unplugged the router or whatever and, boom, it’s back up.

But you’re talking about an entire ecosystem. So because we have the ecosystem instead of a bunch of disparate pieces of technology in there, you’re absolutely right. You make one change. So price would be an example. If we want to change up a price it changes on a kiosk, it’ll change in the POS if they’re using a POS. It will also change on their digital signage, so the menu board above.

Great. We want to change the price. Now let’s say you’re out of avocados. Boom. Now guacamole comes off the menu, so now it’s not even on the menu board if you don’t want it to be. If you run happy hour, great. At 5:00 we change the price, at 7:00 we change it back.

There’s none of that whiteout or cardboard being take up with those changes. We’ve also integrated –

Alan Shimel: [Inaudible comment]

Sam Zietz: – AI and machine learning into it, so based on weather, time of year, time of day, order frequency, items will move up or down on the menu. Because we all go left to right. So what you want to do is you want to feature the most popular items or the items that that consumer’s most likely to order at that point of time to the left so that they can then make their decision quicker and move on in the ordering process.

Alan Shimel: Excellent. Sam, we’re running low on time. I did want to mention, I know you guys recently announced a deal with Samsung, I believe, which is probably one of the largest – I’m going to assume one of the largest kiosk producers in the world – to be powered by GRUBBRR. Do you want to tell us a little bit?

Sam Zietz: Yeah. So Samsung is obviously a very large company. I think they’re the sixth most recognizable brand in the world. They announced on June 30th that they’re entering the kiosk space. I would bet that in short order they will probably be the 800-pound gorilla in the kiosk space. What they’ve really done is they’ve democratized it, bringing that price standpoint down so it’s affordable to everybody.

So you’re going to have a lower price. But traditionally kiosks were kind of hobbled together. They were a shell with a whole bunch of other pieces of technology kind of plugged in to make it look like it was one thing, but it was really five or six things. Samsung has truly built one slick unit that has it all built, which has allowed them to eliminate points of failure so the unit will be more successful. Obviously nobody builds screens as effectively as they do.

In fact, they also have it so from touching it you can’t catch bacteria or COVID or any of that. But the exciting thing for us is, again, as great as a piece of software is, no one is going to buy a kiosk unless it does something, and that’s where we come in. We provide the true value proposition that powers it, and by buying the kiosk with our software you end up reducing OPEX or labor or at least solving for labor when you can’t even find it. More importantly, you increase your revenue.

Typically, our clients see a 12 to 22 percent uplift in average ticket because people will buy more as a result of that curated experience, and we improve customer experience. So those are the value propositions there, but it’s exciting. When you partner with somebody like Samsung it’s not just here in the US. It’s worldwide. And they’ve got unbelievable reach.

Alan Shimel: Oh, yeah. We’ve dealt with them. I mean, just another example, no pun and no irony intended, but software is eating the world. Hey, Sam, you know what we didn’t tell people? Where can get they go get more information about GRUBBRR?

Sam Zietz: Our website’s probably the best place, GRUBBRR.com, G-R-U, double B, double R dot com. So, yeah.

Alan Shimel: Excellent. Alright, man. Hey, say hello to the family. Best of luck with GRUBBRR. Maybe we’ll be ordering somewhere on some GRUBBRR software soon out there. Check it out. Full disclosure. I know Sam a long time, maybe 20 years. Happy to see him doing well with this and playing in the software game. Sam, be well, and we’ll speak to you soon. Come back on and keep us posted.

Sam Zietz: Alright, Al. Thank you again for having me on.

Alan Shimel: Alrighty. Sam Zietz from GRUBBRR here on TechStrong TV. We’re going to take a break. We’ll be right back with our next guest.

[End of Audio]

February 17, 2022
IBM ‘is Ageist and Sexist’ | IBM Mainframe-aaS | IBM Vaccine Mandate

Think! Welcome to Big Blue Week here at The Long View—where we peruse the news of the week and strip it to the essentials. Let’s work out what really matters.

This week: IBM’s employment practices scrutinized, IBM z/OSaaS breaks cover, and IBM encourages staff back to the office.

1. ‘Dinobabies’ and ‘Dated Maternal’ Workforce Woes

First up this week: IBM’s defense in an employment age discrimination lawsuit looks to be shredded. Internal emails “appear to show high-level discussion about paring the ranks of older employees.”

Analysis: Not a good look

According to one of the plaintiff’s lawyers, unnamed “top IBM executives were explicitly plotting with one another to oust older workers … to make room for millennial employees.” On the face of it, they seemed to be doing the polar opposite of the Age Discrimination in Employment Act.

Noam Scheiber: Making ‘Dinobabies’ Extinct: IBM’s Push for a Younger Work Force

Top IBM executives were directly involved in discussions about the need to reduce the portion of older employees … sometimes disparaging them with terms of art like “dinobabies.” … Documents made public by a Federal District Court … show executives discussing plans to phase out older employees.
…
The newly unsealed documents, which quote from internal company emails … show top IBM executives specifically emphasizing the need to thin the ranks of older workers and hire more younger ones. [One] email refers to IBM’s “dated maternal workforce,” an apparent allusion to older women, and says: “This is what must change. They really don’t understand social or engagement.”
…
Adam Pratt, an IBM spokesman, [claimed,] “IBM never engaged in systemic age discrimination.” [He] said that some of the language in the emails “is not consistent with the respect IBM has for its employees” and “does not reflect company practices or policies.”

Yikes, ageism and sexism? Experienced staff are valuable, says MrBanana:

I did some time at IBM [and] remember being invited to a meeting with a new group, headed by a new “thinker,” who had something to present to myself and a colleague. We walked past the foosball table to the meeting room. Naturally the room had no chairs, and was covered in multi-coloured Post-it Notes. Once they had gone through their mood boards and the non-linear presentation of this new idea, I turned to the other old geezer in the room. “Didn’t we look at something like this 8 years ago?”

“Yeah, we worked out that compute power just to run the UI for one session wouldn’t be available for a couple of decades.” The children were somewhat disappointed, and (fortunately) we were never asked back to their romper room.

But experience can be both a blessing and a curse, learned aahortwwy:

I experienced both sides of this in five years at a company in hypergrowth. … I learned so much at that job: … In year 1, I was determined to accomplish X and ignored the skeptical comments of some colleagues who’d been at the company longer than me. I failed and wasted some time. In years 4 and 5, new colleagues were determined to accomplish X and ignored my skeptical comments.

2. IBM Wazi as-a-Service Confusion

“Mainframe” is not a dirty word. It’s secure, vertically scalable, and it put the VM in VMware. Now, what IBM Wazi did for on-prem LPARs, Wazi aaS promises to extend to hosting z/OS instances.

Analysis: Mainframe-as-a-service reinvented

Mainframes and cloud-native DevOps need not be incompatible. To modernize legacy apps using hybrid cloud instances for dev/test—and even prod—can be a big productivity boost. But isn’t it weird that IBM spun out its mainframe-as-a-service zCloud offering only a few months ago?

Mike Vizard: IBM Shifts Mainframe App Testing to the Cloud

While many workloads over the years have been migrated off mainframes or simply retired, the applications that run on z/OS today are still among the most mission-critical that organizations run. … IBM this week revealed it has added the ability to set up testing environments on the IBM Cloud for z/OS mainframe applications.
…
IBM plans to make IBM Wazi as-a-Service (Wazi aaS) for z/OS generally available in the second half of this year, [which] will enable DevOps teams to self-provision an instance of a z/OS virtual server on a secure private space running on IBM Cloud. … At the same time, it will become easier to modernize mainframe applications by making them more accessible to other applications via a set of secure APIs … using a cloud-native set of DevOps tools that run in a Kubernetes environment.
…
Modernizing mainframe applications is a less complicated endeavor than migrating them. The challenge is that building, deploying, maintaining and securing all the APIs required to do so represents a significant amount of effort.

OK, boomer, why are we talking about 1960s mainframes on staging-devopsy.kinsta.cloud? Here’s ArchieBunker:

Mainframes are different beasts altogether, almost alien when you compare them to PC hardware. You have binaries written for the S/360 system in the 1960s? Good news you can still run them natively without a recompile.

You think virtualization and containers are a hot topic? IBM was running multiple OS instances inside a VM in the 1970s. … The engineering is incredible.

But z/OSaaS? It’s déjà vu time for Beleagured Greybeard:

“Cloud Managed Services for z” AKA “zCloud” has been around for over 10 years. … IBM offloaded it with the Kyndryl spin, so its odd that they now want to re-invent it.
…
If it’s a strategic platform, why didn’t they hold onto it instead of spinning it off to Kyndryl? Sounds like yet more daft leadership decisions.

3. IBM’s Return to Work Plan has Vaccine Mandate

IBM wants to “keep employees safe” as they return to office work after being fully remote. In practice, this means a vaccine mandate.

Analysis: IBM Digital Health Pass is divisive to vocal minority

Although there are exemptions on medical or religious grounds, IBM has promised to place dissenters on unpaid leave. As you might expect, the policy has a few employees up in arms.

Cassie Werber: How Salesforce, IBM, and HSBC are approaching return to work

When the pandemic hit, and IBM moved 95% of its workforce to fully remote, it was pleasantly surprised to discover no drop in productivity. … Still, they planned to return to offices.
…
The company saw this as a way to keep employees safe. … One example … is its development of the IBM Digital Health Pass as an alternative to vaccine cards or paper vaccine certificates, which they use to make sure all the staff that come into their offices are vaccinated.
…
Arvind Krishna, IBM’s CEO, meanwhile came up with what he called the IBM Work From Home Pledge. [It] included commitments to flexibility, kindness, sensitivity to family, setting boundaries, and acknowledged video fatigue. It concluded with a commitment to “be connected.”

Tricky to “be connected” if you’re not allowed back in the building. Anne D’Innocenzio, Heather Hollingsworth, Tali Arbel, Mae Anderson, Ken Sweet, Matt O’Brien and Dee-Ann Durbin:

IBM software engineer Justin Albano said his company recently notified employees that it would be revoking badge access to workers who aren’t vaccinated or haven’t proved that they are. “We’re not able to enter an IBM office at this time,” said Albano.
…
He said some workers have successfully sought religious exemptions but “my thought process was I shouldn’t have to explain to my company my faith” to get out of a policy that’s “immoral in its foundation.”

What’s the alternative? With a perspective, it’s Chris Haney:

Or, get the vaccine. Protect yourself and the people around you. You people really are detached from reality.

The Moral of the Story: Those who know do not speak; those who speak do not know.

You have been reading The Long View by Richi Jennings. You can contact him at @RiCHi or tlv@richi.uk.

Image: Marcin Wichary—cc:by; leveled and cropped (ask your parents)

February 17, 2022
Cloudify Integrates DevOps Automation Platform With Terraform

Cloudify this week announced a free user interface (UI) module that extends its infrastructure provisioning platform and enables DevOps professionals to integrate unlimited Terraform modules.

Nati Shalom, Cloudify CTO, said Terraform UI provides a familiar construct for DevOps teams using the open source DevOps automation platform to provision infrastructure-as-code (IaC). The module enables DevOps professionals to seamlessly import Terraform modules to Cloudify without writing blueprints or any additional glue code, he said.

Cloudify now automatically generates the wrapper required for each Terraform template to enable DevOps teams to collaboratively manage secrets, execute concurrent deployments, store states remotely and monitor deployments, users and versions via any Git repository. Those Terraform modules can then be integrated with application programming interfaces (APIs) and continuous integration/continuous delivery (CI/CD) platforms as DevOps teams require.

DevOps teams can also import existing automation modules and scripts into Cloudify. Those modules and scripts can be automatically converted to environments that can be centrally managed via the Cloudify console or via export to ServiceNow’s IT service management (ITSM) platform as a software-as-a-service (SaaS) application.

That approach provides the added benefit of enabling DevOps teams to centrally manage all Terraform modules and versions via a single console as part of an effort to reduce misconfigurations that lead to security breaches, he added.

Cloudify enables DevOps teams to create a self-service catalog and portal through which infrastructure can be managed. Many DevOps teams have built their own portals to manage this process. However, Shalom noted those DevOps teams then need to devote resources to maintaining that portal when those resources could be allocated to other critical tasks.

DevOps teams can not only use Cloudify to apply patches, change topologies, add security features, make configuration changes or make additional resources available, Shalom added, they can also now integrate Terraform tooling with platforms such as Kubernetes or other automation frameworks such as Ansible. Cloudify also makes available an enterprise-grade version of the platform with these integrations.

It’s not clear how much time and effort IT organizations are investing in building and maintaining DevOps environments. In many cases, however, organizations should probably revisit decisions about building capabilities that, at the time, didn’t exist. That doesn’t necessarily mean that replacing custom DevOps tools makes sense across the board, but it is likely that, in the intervening years, the range of tooling made available via DevOps platforms has greatly expanded. Relative newcomers to DevOps, meanwhile, are enjoying the benefit of platforms they did not have to construct themselves.

In fact, Shalom noted that, in terms of DevOps adoption, an inflection point has been reached as more organizations launch digital business transformation initiatives that require applications to be both built and deployed faster than ever. The challenge, of course, is enabling that to occur both safely and at a reasonable cost.

February 17, 2022