Deployment automation is critical to practicing effective DevOps. Without deployment automation, releases still require a lot of manual steps and processes. Processes and steps that aren’t reliably repeatable, are prone to human errors, and can’t be handled consistently with high frequency.

However, the software best practices can’t simply be grafted onto database deployments. Unlike software code, a database isn’t just a collection of files. You can’t simply copy a database among your different development, testing, and production environments. Deploying a database also presents a greater business risk since it holds your most valued asset – your data.

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Which of the following best describes how you currently monitor and manage systems across your hybrid cloud environment?(Required)

Multiple separate tools for different environments

Multiple separate tools for different monitoring and management functions

Single consolidated dashboard

Custom built monitoring and management solution

No full monitoring and management solution

Don’t know

How valuable would it be for your monitoring and management solution to incorporate predictive analytics to help you identify and address system issues that are critical and not waste time or effort working through all the data and “noise” that is not critical?(Required)

Extremely valuable

Moderately valuable

Somewhat valuable

Slightly valuable

Not valuable

How do you most typically address potential system issues BEFORE they impact your operations?(Required)

Automated workflows and playbooks to remediate potential issues as soon as they are detected

An orchestrated response process that leverages automation, AI, and human expertise to rapidly respond to potential issues

Advanced monitoring tools such as predictive analytics and anomaly detection to proactively identify and address potential issues

Respond to issues as they arise, using manual processes and troubleshooting techniques

A combination of automated remediation, orchestrated response, and/or proactive monitoring to address potential system issues

Don’t know

Other

What methods does your organization use to control and monitor cloud/IT spending?(Required)

Centralized procurement processes

Pre-approved budget thresholds

Automated cost monitoring tools

Department-level spending controls

Regular cost audits and reviews

Cloud cost optimization platform

Approval workflows for resource provisioning

Native financial operations tools provided by the cloud provider

No formal controls in place

Don’t know

Other

Please specify:

Which methods do you rely on most to detect security vulnerabilities in your systems?(Required)

Automated scanning tools

Manual assessments

Vendor notifications

Threat modeling (for early detection)

None of these

Don’t know

Other

Please specify:

What are the TWO most common ways you prioritize vulnerabilities to address within your environment?(Required)

Based on potential impact

Based on exploitability

Regulatory compliance requirements

Based on CVSS scores

Risk-based analysis of multiple factors

First-in-first-out approach

No formal prioritization process

Don’t know

How do you typically handle system updates and security patches?(Required)

Automated updates and patches

Manually review and apply updates and patches on a regular schedule

A combination of automation and manual review

Apply updates and patches on an as-needed basis.

Outsourced update and patch management

No defined process

Don’t know

Other

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In order to capitalize on DevOp automation advantages for databases and to promote database changes safely and quickly, all the particular components of a database; its tables, functions, and content, need to be protected.

Any successful DevOps database automation solution must be capable of intelligently dealing with conflicts and merges of code and cross updates from other teams. The solution must be able to ignore wrong code overrides and give the user ultimate control over which changes and merges are pushed out.

In order to achieve these goals a DevOps for the database solution must be able to conduct a three-way analysis on the source (that is, the object after the development work is done), the original (or “baseline”) state, and the target (or “Production”) environment, identifying the differences among these three states. Team members, gaining full knowledge of the complete scope of the project from the analysis, can review the results and options the solution presents to resolve any discrepancies. The user selects what action, if any, should be taken on the database. The solution then automatically generates the scripts to execute the chosen actions.

In this way, the solution uses automated three-way analysis and automatic script generation to eliminate both the potential for human error in manual script writing, and the potential for technological error in automated object overrides.

Reaping the Rewards
Implementing a solution that encompasses all these automation features to meet the particular challenges of database deployments, would enable a company to practice a DevOps approach to effective database automation and realize the following benefits:

· Reduced deployment costs through streamlining of development process management

· Minimizing deployment risks by enforcing change policy and best practices, and configuration management and consistency

· Improving responsiveness to customers and market needs with speedier roll-outs of task-based development updates

· Enhancing cross-team communication with clear audit trails and transparency regarding work done on objects and the state of different environments

Can you afford to be without it?

About The Author ⁄ Yaniv Yehuda, CTO, DBmaestro

Yaniv is the Co-Founder and CTO of DBmaestro, the leading provider of DevOps for Database solutions which enable control of database development and deployment. Yaniv is also the Co-Founder and the head of development for the Extreme group, a leading IT services solutions provider group.