How to Optimize Your Cloud Services Cost
In this blog post, we review some of the biggest risks behind increasing services cost and how to optimize cloud services cost with a proper application monitoring solution.
As modern software deployments continue to break down into smaller and more modular units, the world is seeing more moving parts in the deployment equation. The drivers behind digital transformation and modernization of software are clear: accelerating innovation, optimizing the customer experience, competition, and reducing unnecessary spending.
What’s the downside of all this technical innovation and sophistication? Cost.
As you continue to adopt, re-factor, and deploy your new microservices, you will increasingly begin to experience microservice sprawl. Further, your teams are breaking up into smaller teams as both your services and engineering teams become more distributed.
Epsagon’s Service Map for Microservices
A single click or tap can invoke dozens of synchronous or asynchronous events to fulfill that request across hundreds, sometimes thousands, of services. This exposes your teams to search for a needle in a haystack when trying to diagnose application issues in production.
The response time of your application is dependent on all services — deployed in any cloud — maintaining optimal performance so as not to increase your application response time and cloud services cost. You need to be able to trace the call across multiple services and — equally as important — also need the diagnostic data necessary to immediately resolve and redeploy your code.
Epsagon’s Trace Search
With properly distributed tracing capabilities in place, you have insight into diagnosing application issues in fractions of the time. Rapid diagnosis means rapid fixing and lower cloud services cost.
Cloud Migration & Adoption
According to a 2020 Progress report, 56% of respondents are in the process of — or currently planning — their cloud migration initiatives. During the process of your migration and adoption of a multi-cloud deployment, maintaining observability into the end-to-end performance of your deployment is key to optimize performance and services costs. Specifically, you want to ensure that you have the capabilities and strategy in place to understand which service — and in which cloud — is the issue and why its performance is affecting other services and increasing your services cost.
Without proper visibility, engineers and operators tend to overprovision their servers, increasing services cost. Many performance issues are caused by poorly written code, including:
- Memory leaks
- Network I/O blocks
- CPU over usage
- Maxing out HDD capacity
With thousands of services across an organization, overprovisioning cloud resources can cost organizations millions of dollars in unnecessary computing power.
Continuous Deployment and Delivery
Modern software environments continue to support independent release pipelines for software teams owning individual services. This is important because of the correlation of your ability to innovate and your business success. In layman’s terms: better features means better business.
Unfortunately, each pipeline — potentially thousands of them — can increase the possibility of introducing performance degradation into production.
Increasing Release Velocity with Monitoring
Maintaining an optimal release velocity requires continued investments in your DevOps teams. Modern environments are reaching deployments of multiple times per day with extremely short lead times. Your deployment velocity is critical to remain relevant and competitive by building new services and optimizing cloud services cost.
Maintaining performance monitoring throughout each stage of your SDLC, specifically during production releases, serves as a safety-net to this level of a next-generation release cadence. Without visibility into performance, you run the risk of downtime, and downtime can cost your business millions in lost revenue. For businesses like yours, this could be thousands of dollars per minute.
The right monitoring solution to optimize cloud services cost
Considering all of the above, you want to ensure the following critical capabilities from your monitoring solution.
LIghtweight Agents & Automated Monitoring
The manual work involved in configuring, deploying, and maintaining traditional agents that rely on bytecode instrumentation can easily spiral out of control. Developer time can be wasted on unnecessary code changes and custom performance hacks to maintain visibility. Open-source projects require engineering efforts and implementation costs to piece together a mashup of tools.
With Epsagon’s lightweight agent SDK for rapid onboarding and automated monitoring, you can keep up with the number of services your organization supports. We’ve combined the ability to monitor and optimize your services across your distributed calls and logging for modern environments.
Your services continue to deploy across multiple clouds, including AWS and Azure. Some of your developers are already building using serverless technology, such as Lambda, and orchestration tools like Kubernetes, ECS, and Step Functions. The benefits of these technologies are clear, but the risk is high when a single point of failure is introduced within the anatomy of a highly distributed request.
With Epsagon, you have the necessary visibility into tracing any distributed calls among any number of services, devices, and APIs in order to rapidly triage, diagnose, and resolve application issues in real-time. Software issues that may take days to diagnose can now be resolved within minutes and hours., thus decreasing services cost.
Cloud Cost Visibility
As you further migrate your services into the cloud, overprovisioning computing resources is a common pitfall that can cost organizations millions of dollars in unnecessary spending and services cost. Without proper visibility into application performance, overprovisioning is a tactic that developers can use to “throw costly resources” at the problem. Unfortunately, if these resources are never used, you’re stuck with a high cloud bill.
With Epsagon, you can set alerts for resources and view performance over time allowing you to optimize for the usage of your compute services, as well as see estimated monthly costs for AWS Lambda functions.
Pay for Usage, Not Hosts
Most performance monitoring solutions approach pricing based on hosts, punishing organizations that are undergoing modernization tactics to their monolithic software. This outdated pricing model was not designed for modern and distributed application deployments and is associated with high application and services cost.
We at Epsagon believe in charging based on optimized usage, not hosts, so you can fix issues fast and keep services cost down. We believe in democratizing performance monitoring, so we don’t peg our pricing to your modernization initiatives. You can visit our pricing page to learn more.
Epsagon’s Dashboards with Key Performance Metrics
Optimize Your Cloud Services Cost – Summing it up
Modernizing your applications can potentially increase your services cost. However, maintaining proper performance observability into your applications with Epsagon means that you can decrease common costs with the modernization and deployment of modern software architecture.
With Epsagon, you have the right observability platform in place and the necessary visibility to be a harness as your applications continue to adopt modern architecture practices.
Ran Ribenzaft is the Co-founder and CTO of Epsagon and also an AWS Serverless Hero. Ran is a passionate developer with an army elite intelligence-unit background, and vast experience in network, infrastructure, and cyber-security. He is constantly chasing new technologies and loves sharing open-source tools to make lives easier. @ranrib
Epsagon’s SaaS platform allows Dev and Ops teams to troubleshoot less and fix issues faster by providing automated data correlation, payloads, and end-to-end observability within microservice environments. With a lightweight agent SDK, Epsagon provides automated instrumentation and tracing without gaps in coverage, giving you full visibility for containers, VMs, serverless, and more with no training, manual coding, tagging, or maintenance required.