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Test Environment Stability | @DevOpsSummit #APM #CloudNative #Monitoring

Find confidence in the systems you are delivering

How often is an environment unavailable due to factors within your project's control? How often is an environment unavailable due to external factors? Is the software and hardware in the environment up to date with the target production systems? How often do you have to resort to manual workarounds due to an environment?

These are all questions that you should ask yourself if testing environments are consistently unavailable and affected by outages. Here are three key metrics that you can track that can help avoid costly downtime.

Metric: Availability and Uptime Percentage
QA and staging environments seldom require the same level of uptime as production, but tell that to a team of developers working 24/7 on a project that has an aggressive deadline and you will have a very unhappy team. As a test environment manager, you know that when a QA system is unavailable, you get immediate calls from developers and managers.

Understanding why an outage happened is critical for communicating with a development team. If you follow a problem management process for production outages, similar to the process throughout the rest of your IT environment, then you should also follow this process with test environment management. Very often a QA environment will become unavailable due to a factor outside the control of a test environment manager. If one team pushes bad code that interrupts the QA process for all teams you need to be able to identify this clearly.

How to measure availability and uptime?
To truly understand availability and uptime, you must keep track of system availability with a standard monitoring tool such as Zabbix or Nagios. If your systems are visible to the public internet, you can also use hosted platforms like Pingdom to measure system availability.

An uptime of 95% is usually sufficient for a QA or staging environment. If your development is limited to a few time zones, you can also further qualify this by only measuring availability during development hours. While production availability commitment is often closer to 99% or 99.5%, you don't have to treat every QA outage as an emergency. But, be aware that developers may have other opinions-95% uptime still allows for eight hours of downtime a week, so it may be best to aim higher.

How does this metric motivate concrete action?
When you measure system availability and make these numbers public, you encourage test environment managers to make a commitment to uptime. This results in fewer obstacles for QA and development, allowing them to deliver software faster. There's nothing more debilitating to an organization than disruptions in QA and testing. Keeping a close eye on availability and tracking as a metric also encourages movement towards always-available QA systems.

Metric: Mean Time Between Outages
If a system has a 95% availability, then almost 75 minutes of downtime is acceptable every day. If the system fails for ten minutes every hour during an eight-hour work day due to a build or deployment, you'll be creating a QA or staging environment that has a 5% chance of losing developer and QA confidence. To get an accurate picture of system availability you need to couple an availability percentage metric with the mean time between outages (MTBO).

How to Measure MTBO?
If you follow a process that keeps track of outages and strives to understand the root causes of these outages, you'll amass a database of issues that can be used to derive the MTBO. With a monitoring system configured to calculate availability percentages automatically, you can use this same system to record your MTBO.

Example Metric: Goal for MTBO
A goal for MTBO, depends greatly on your availability goal. The lower your availability goal, the higher your MTBO should be. For example, if you have a 95% uptime commitment then your outages need to be spaced over a day or a week. You might have eight hours of downtime each weekend to perform system upgrades or a nightly build and deploy process that takes about an hour, but what you can't have is an MTBO of 45-60 minutes. This will mean that QA and staging systems will be unavailable for a few minutes every hour, which will result in dissatisfied customers.

How does this metric motivate concrete action?
If your MBTO is very short, this suggests that build and deploy activity from a continuous integration environment is frequently interrupting both development and QA. If your MBTO is very high, but your availability is very low (95% or lower) this means that you are experiencing multi-hour downtime at least once a day.

When measuring MBTO, encourage your release engineers and test environment managers to work together to create build and deployment scripts that don't affect availability, and encourage staff to approach QA and staging uptime with care. Without this metric, you run the risk of having teams grow complacent with frequent, low-level unavailability as long as they satisfy overall availability metrics.

Metric: Downtime requirement for a test environment build and deploy
When software is deployed to any system, there is a natural tendency for disruption. If new code is being deployed to an application server, that server often requires a restart so that new code can be loaded. If a web server, such as Apache or Nginx, is being reconfigured this often requires a fast restart measured in seconds.

Some of these build and deploy related disruptions can be avoided through the use of load balancers and clusters of machines. On the largest projects, this is essential in both production as well as staging and QA systems.

An example is a QA system for a large bank's transaction processing system. There are so many teams that depend on this system to be up and running 24/7 that causing any disruption would run the risk of freezing the QA process across the entire company.

Other build and deploy downtimes are unavoidable. A frequent example is when there are changes to a database schema. Certain changes to tables and indexes require systems to be stopped and rebooted to reach a state where database activity isn't competing with DDL statements.

The downtime requirement for a given build and deploy to a test environment is a central measure that is directly related to the availability metrics already discussed.

How to Measure Build/Deploy Downtime?
It's simple: run a build and deployment and keep track of the downtime that falls into the timespan of each build and deploy function. If you have a continuous integration system, such as Jenkins or Bamboo, grab the timestamps of the last few builds and look at your monitoring metrics on QA and staging to see if there is a system impact.

Example Metric: Goal for Build/Deploy Downtime
Your goal for this metric depends on your level of availability. If you are working on a shared service, build and deploy downtime requirements should be as close to zero as possible. If you are working on a less critical application, then build and deploy downtime should be measured in minutes or seconds.

How does this Metric Motivate Concrete Action?
This metric encourages release engineers and test environment managers to drive build and deploy downtime to zero. With the tools available to developers and DevOps professionals, it is possible to achieve zero-downtime deployments to QA and staging systems. Doing this will give internal customers more confidence in the systems you are delivering.


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More Stories By Dalibor Siroky

Dalibor Siroky, CEO and Co-Founder, Plutora: Dalibor has close to 15 years of leadership, consulting, enterprise product, and operations experience in Australia, Asia, and Europe. Before co-founding Plutora, Dalibor was the founder and managing director of Finotaur, a leading provider of independent management consulting services to Wealth Management, Investment Management, Private Banking, and Payment institutions within the Asia Pacific region. Earlier in his career, Dalibor served as the CIO of financial advisory software at Macquarie Bank, head of solution architecture at Commonwealth Bank of Australia, and as a management consultant at PricewaterhouseCoopers. Dalibor holds an MS in Software Engineering with distinction from the University of Oxford and an MBA with honors from the University of Chicago. Dalibor is also a graduate of the Royal Military College of Australia and served as a Captain in the Army.

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