The tech world isn’t static. As soon as you get comfortable with a technology or a way of doing things, something new and more innovative shows up. With these constant changes, enterprises have to make sure they are always enhancing their IT infrastructure to get the most out of it. Enterprises everywhere have been modernizing their workloads for a long time now. However, this modernization can be tricky. You need to figure out which platforms to use, which vendors to trust, and which tools to add to your toolbox to help with tasks like automation and monitoring. Modern architectures are diverse and dynamic, which for many organizations includes maintaining various clouds. And this, of course, makes monitoring multicloud apps that much harder
Why has monitoring gotten harder?
This question is not hard to answer and any organization that has migrated its traditional workloads would be able to answer it in depth. Monitoring has always been very critical because it gives developers and ops teams insight into what’s happening with their applications and infrastructure. However, with modernization, the workloads are getting complex. With the rise of hybrid and multicloud approaches, there’s so much area to be covered to get real-time monitoring data. This complicates things for developers as they have to now work to find ways to monitor their workloads taking the focus away from other important work. Even if an organization finds a way to collect different metrics from different platforms, visualizing data is not a walk in the park.
Need for visualizing monitoring data
Data visualization is important for any organization, especially in the context of monitoring multicloud apps. Data visualization gives users insight into their data and how it is being used. Visualizing your data allows you to find patterns, trends, and relationships in your data to help you make informed decisions.
The same goes for monitoring data. Possible metrics can range from application performance to network usage to memory consumption. These metrics should be visualized properly so teams can stay on top of any issue that could hamper the infrastructure availability. Organizations should decide what metrics to measure so that they can make the most of all their monitoring data. However, the question remains — how do you visualize metrics from multiple platforms to gain end-to-end visibility?
Monitoring challenges for multicloud apps and their solutions
Your infrastructure could be multicloud or hybrid or you might have a CI/CD or GitOps pipeline in place. Let’s see how you can empower your metrics with data visualization.
Multicloud or hybrid platforms
There are so many advantages to hybrid and multicloud platforms. This is the reason organizations are increasingly investing in maintaining a diverse cloud-native architecture. However, there are a lot of challenges when it comes to monitoring. Organizations opt for these infrastructures to enjoy flexibility. However, the easier it is to modify the architecture based on a change in requirements, the harder it gets to have a monitoring solution in place.
Most organizations depend on monitoring solutions provided to them by their public cloud vendors, but these solutions only monitor that particular vendor’s platform – for example, CloudWatch for AWS. In this case, organizations may find themselves investing in different solutions for different clouds which isn’t ideal. This gets worse when you have a hybrid platform in place. You’ll end up setting up separate solutions for the private cloud and your on-prem infrastructure. Some organizations also try extending the monitoring solutions they use for their datacenters to monitor their cloud-based workloads. However, these tools are usually limited and may not offer accurate metrics to visualize monitoring data.
There are solutions available in the market that address the monitoring challenges in hybrid and multi-cloud stacks. Solutions like New Relic, Dynatrace, and ThousandEyes help organizations monitor their applications regardless of which cloud platform they’re run on. These tools help identify relationships in real-time and visualize them on a single pane of glass. These solutions help you identify issues early on so that you can remedy them quickly. These monitoring solutions also allow you to freely modify your architecture without having to worry about constant configuration, thereby giving developers the time to focus on more important tasks.
Monitor your CI/CD pipelines
DevOps teams are rapidly adopting CI/CD pipelines to speed up deployments up to multiple times a day. Although CI/CD pipelines offer unmatched speed, they also introduce new challenges concerning monitoring. With continuous releases, the number of issues or errors also increases which is problematic. Having a good monitoring logic in place that automatically senses these issues and alerts users in real-time is quite important.
CI/CD pipelines don’t allow much time to dwell on developing monitoring logic manually. If performance issues go unnoticed during build and unit tests, they are bound to show up later. At this stage, they take a long time to fix, which can slow down a deployment and leave you back at square one. Hence, you need to deploy automated application monitoring solutions at the very early stages of your pipeline to quickly fix any issues.
Apart from this, monitoring your entire pipeline is also very important. A CI/CD pipeline monitoring solution will help enhance your delivery pipeline by bringing all the different exceptions to light on a single interface. This way, it’s not just the QA team that’s responsible for testing, but everyone on the team will be able to see the exceptions and deal with them. This knowledge of possible exceptions can help resolve issues during the build phase itself. This ensures no time is wasted on reverting releases fraught with bugs.
Advanced tools like SignalFx’s CI/CD Monitoring provide real-time visualization of canary and blue-green releases. These solutions also notify users about code pushes and if they need to manually address an issue. Such solutions also allow you to visualize various events in your delivery pipeline for complete observability. You can simply share dashboards across teams and collaborate with different team members.
Monitoring Kubernetes clusters
Containers have changed the way applications are developed. Kubernetes has emerged as the leading container orchestration tool in the market. However, Kubernetes can get complicated when it comes to creating, deploying, and running multiple clusters. This complication also applies to monitoring. An organization can have multiple clusters all having numerous pods. Applying monitoring manually to each pod or an entire cluster can get frustrating. However, if you use Kubernetes in production, you can choose from a wide variety of open-source Kubernetes monitoring tools for observability.
Prometheus is one of the most popular Kubernetes monitoring tools. With Prometheus, you get a time-series based multi-dimensional data model that can be queried via PromQL to retrieve required metrics. Rule-based alerts can be set up so which saves developers’ time and efforts. To help visualize monitoring data, Prometheus comes with integration for Grafana.
Monitoring multicloud apps: Try different tools to find the right one
There’s no one-size-fits-all when it comes to solutions for monitoring multicloud apps. To find the right tool, you need to try different tools until you find ones that can address your monitoring challenges. Multiple monitoring solutions may be required for stacks involving multiple cloud platforms and modern architecture. In the end, you need to build a monitoring infrastructure that is capable of real-time monitoring and accommodates changes easily so that you have true end-to-end visibility.
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