Cloud enablement, Digital strategy

Cloud monitoring in the DevOps world

Cloud monitoring in the DevOps world

Coupling the cloud with a DevOps culture can often be key to optimising productivity and meeting your technological goals. 

With the cloud being an effective approach to ensuring scalability and adaptability in today’s working world, coupling it with a DevOps culture can often be key to optimising productivity and meeting your technological goals. 

You can think of DevOps as a culture built around related practices and toolsets. A key benefit of DevOps is that it shortens the development lifecycle because the development and operations teams are more aligned and collaborate from the start of a project. The DevOps model relies on effective tooling to help teams rapidly and reliably deploy and innovate for their clients. These tools automate manual tasks, help teams manage complex environments at scale, and keep engineers in control of the high deployment velocity that is enabled by DevOps.

But, more often that not, businesses are using the cloud as part of their overall technical landscape and to meet their strategic goals.

One of the places that DevOps and the cloud intersect is cloud monitoring. As the system grows bigger and release cycles shorten, it’s important to ensure that engineering teams have access to (near) real-time information. This ensures that subsequent changes are based on the true state of an environment.

What is cloud monitoring?

Cloud monitoring uses manual and automated tools to monitor, analyse and report on the availability and performance of websites, servers, applications and other cloud infrastructure. For example, cloud monitoring tools enable you to test an application for speed, functionality, and reliability to help ensure that it is performing optimally.

Cloud monitoring is generally performed as part of an overall cloud management strategy, enabling IT administrators to review the operational status of cloud-based resources. It also provides a holistic view of cloud metrics, customer interaction with the system (real user monitoring), log data and more.

Best practices

Based on almost 40 years’ experience as an international software development company, and many successful cloud implementations under our belt, adopting these best practices help us achieve optimal cloud uptime and performance:

  • Identify key performance indicators (KPIs) and other metrics that affect your business’s bottom line and the overall user experience. When it comes to cloud environments, there’s a lot to monitor, but not everything warrants close attention. Designating which KPIs and metrics you want to track prior to implementing a cloud monitoring strategy will give you a clear sense of what to prioritise.
  • Group underlying components into their applications and map them to relevant business services. Given that cloud environments are highly complex, it’s critical to understand the relationships between individual resources and build that information into the monitoring system. This allows for a more comprehensive understanding of how an issue within one component might affect the broader application and, more importantly, business and end-users.
  • Keep a close eye on cloud service usage and fees. The beauty of cloud computing is that it’s highly scalable. But increased usage can result in higher costs, so make sure your cloud monitoring solution is tracking usage activity and associated costs. In an ideally architected and configured environment, usage costs should not increase in lockstep with user activity i.e. there are economies of scale that can be benefitted on by using the cloud.
  • Establish good baselines. Different applications have different base activity levels. It’s important that you know what constitutes as normal for each so that your cloud monitoring solution automatically scales your computing infrastructure to maintain peak performance levels if an app exceeds its baseline or to keep costs down if it falls below.
  • Consolidate all data within a single, centralised platform. It’s important that all your cloud monitoring data – including data pulled from multiple different sources – live in one place so it’s easily accessible (for further processing) and consistent, and so that you have a holistic view of cloud performance.

AWS tools to accurately monitor cloud environments

In the case of environments built on AWS infrastructure, these are some of the tools we use for successful delivery:

  • CloudWatch is a monitoring and management service that provides data and actionable insights for AWS, hybrid, and on-premises applications and infrastructure resources
  • Grafana is an open-source solution for running data analytics, and ingesting metrics that make sense of the massive amounts of data our systems generate. It facilitates the monitoring of our apps by summarising useful information with the help of cool, customisable dashboards
  • Prometheus is an open-source and community driven performance monitoring solution. It also supports container monitoring and creation of rules which trigger alerts based on time series data
  • AppDynamics facilitates real-time insights into application performance. This DevOps tool monitors and reports on the performance of all transactions flowing through your application
  • DataDog is an observability service for cloud-scale applications, providing monitoring of servers, databases, tools, and services, through a SaaS-based data analytics platform
  • Splunk is a software platform widely used for monitoring, searching, analysing and visualising machine-generated data in real time. It performs capturing, indexing, and correlation of the real time data in a searchable container and produces graphs, alerts, dashboards and visualisations
  • Loki is a horizontally scalable, highly available, multi-tenant log aggregation system inspired by Prometheus
  • AWS Xray is a service that helps engineers analyse and debug distributed applications by enabling them to follow requests as they flow through the system. X-Ray is used to monitor application traces, including the performance of calls to other downstream components or services, in either cloud-hosted applications or from their own machines during development
  • OpenTracing (Jaeger) is open-source software for tracing transactions between distributed services. It’s used for monitoring and troubleshooting complex microservices environments

Adopting a DevOps culture alongside your cloud environment can be key to helping businesses effectively deliver resilient services and applications at a rapid pace. If you’re looking for a software development partner with extensive experience implementing both the DevOps culture and cloud deployments, reach out to us.

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