Breaking Down Communication Barriers With Observability
Communication might be hampered by a lack of understanding of the language. Opposing interests can do the same. “Numbers don’t lie,” as the adage goes. You can’t argue with facts, whether you like them or not.
At 27Global, we use data daily to break down communication barriers between our globally dispersed development teams, our development and site reliability engineering (SRE) teams, and ourselves and our clients. Productivity and quality decrease when communication is hampered. That is why data is so vital to our SRE team. SRE is a business pillar of 27Global, utilized internally to assure high performance and quality in our development projects and service provided to clients to monitor and respond to issues in their production workloads.
The SRE function is mission-important for our clients and us, and having complete, reliable telemetry data is critical. The problem is obtaining that information without imposing additional work on our engineers, who must focus on providing excellent products. To meet that challenge, you’ll need a lot of observability and automation across the board.
Why is it essential to have observability across the stack and programmability?
Thanks to observability, we have a single version of the truth to share with our worldwide development teams—the ability to evaluate and troubleshoot problems across your whole software stack quickly. But it isn’t only for our programmers. It also gives us visibility and insight into production workloads, which frequently reveal performance issues like delayed queries, resource congestion, and queuing bottlenecks that would not appear in a test environment and are nearly impossible to recreate by our development team.
Everything, everywhere—on-premises, in the cloud, virtualized, containerized, monolithic, microservices, you name it—observability encompasses application performance monitoring, infrastructure monitoring, log analytics, and digital experience monitoring. Instrumenting to collect and visualize data from these places should be done programmatically if you don’t want to burden your engineers with manually creating all those alerts. You want to provide APIs so that people can program instrumentation into the product and automate alerts. It minimizes toil, and lowering toil allows our employees to be more productive and focus on meaningful work rather than low-level activities.
Let’s look at some of the concrete things we’re doing to collect the data we need, not only to break down communication barriers but also to increase productivity and product quality and provide genuine value to our SRE clients.
Observability as code for automation
For provisioning and controlling infrastructure as code, we rely on Terraform. Ansible is also used to automate application development. Our cloud engineers had to add monitoring to the infrastructure manually, and our developers had to embed monitoring into the applications in the past. We now use APIs to integrate tracking into our applications and infrastructure automatically. It is referred to as observability in code. For example, when setting up a new Kubernetes pod, we can use Ansible. Then we can layer variables on top of it. Instead of reinventing the wheel each time, it gives us a template that we can use repeatedly.
From a DevOps standpoint, automating—with observability built into the environment—allows us to move much more quickly. Furthermore, as previously stated, it reduces toil, which is something that no developer appreciates. It will enable individuals to focus on more exciting projects by reducing their time on tiresome jobs.
Creating dashboards to help multinational teams communicate more effectively
We can obtain a lot of valuable data by instrumenting applications and infrastructure. Data eliminates communication issues, so there are no more excuses. May use data in various ways to improve communications, one of which is dashboards.
For our development teams, we created end-of-day dashboards. As do most modern IT shops, we have many groups spread across different physical locations, time zones, and countries. Using a consistent data set to promote effortless communication amongst our remote teams is a terrific approach to save time. Transferring one group to the next is significantly easier when daily operational data is rolled up into dashboards. It is in favor of a sun-following model like ours. Instead of trying to communicate information to several people individually, everyone has a single point of contact. They all have the same perspective of the same data, allowing us to maintain a higher level of consistency as projects are handed over at the end of each day.
Dashboards also help to break down communication barriers between development and SRE teams. We attempt to provide our developers visibility into consequences on-site stability, just as we expect them to design deployable code. This visibility gives the development team a better understanding of the SRE team’s requirements. The same is true for SREs, who can better understand developer activity. Data is a method for both parties to meet in the middle with a shared set of measurements that brings teams together to have the same conversation, which is a significant gain.
Increasingly working and cutting down on problem-solving time (MTTR)
One of the best features of an observability platform is that it gives you a unified view of your surroundings. In 30 seconds, we can “wow” a client by displaying them a Kubernetes cluster with all of the services, nodes, and namespaces. We can now provide clients with real-time metrics on uptime, performance, and digital user experience, whereas previously, gathering all of this data would take four hours or more.
Internally, we’ve seen an increase in productivity. Utilizing a combination of full-stack observability and automation, we’ve cut the time it takes to set up a new project in half, and that time continues to drop.
The time it takes to resolve a problem is also shorter. One of our clients, for example, experienced a database issue. We were able to troubleshoot a problematic query the next day and correct it. The customer immediately noticed a significant improvement in the application’s performance.
This example illustrates a fundamental benefit of our SRE service: swiftly identifying and resolving application and infrastructure issues. We want to recognize and respond to concerns with our clients before they affect their customers.
With a data-centric strategy, there are no communication issues.
As you can see, full-stack observability and automation significantly impact 27Global’s product and service performance and quality. We don’t have any communication issues because we have the evidence to back up our assertions. We can adequately assess critical operational aspects of apps and infrastructure, get valuable insights, and share those insights in real-time. With a programmable observability platform, we can acquire a lot more valuable data without putting in the extra effort. Any DevOps team will be grateful for it.
Enteros
About Enteros
Enteros offers a patented database performance management SaaS platform. It proactively identifies root causes of complex business-impacting database scalability and performance issues across a growing number of RDBMS, NoSQL, and machine learning database platforms.
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