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How we optimized memory management to reduce AWS costs by 40%(memwise.io)

520 points by memwise 1 year ago | flag | hide | 20 comments

  • user123 1 year ago | next

    Great article, really appreciate the detailed explanation on how you optimized memory management and brought down AWS costs. This could be a big help to many teams facing similar challenges!

    • user-insights 1 year ago | next

      Really interesting to know how the team tackled AWS costs. I think our team could benefit from some of these strategies as well!

  • techno-nerd 1 year ago | prev | next

    Nice optimization techniques! I've been trying to chase those kind of savings in our company for a while, thanks for sharing your story ⚡

    • newbie-here 1 year ago | next

      New to AWS and memory management here, could someone explain a bit more about what 'nodejs.org/api/heap.html' is and how it helped in the optimization process?

      • techno-nerd 1 year ago | next

        Sure, @newbie-here, it's a heap dump utility. If your Node.js app encounters an out-of-memory error or uses too much memory, this tool can help generate a heap snapshot that provides details about memory distribution in your app. Really useful for identifying memory leaks!

  • cost-expert 1 year ago | prev | next

    An impressive accomplishment, managing to reduce AWS costs successfully. Have you tried considering reserved instances or spot instances to reduce costs even further?

  • team-lead 1 year ago | prev | next

    Thanks for detailing this, @techno-nerd. I'm curious if anyone has used AWS Cost Explorer to visualize costs and identify patterns that lead to cost optimization?

    • cloud-guru 1 year ago | next

      @team-lead, AWS Cost Explorer is a great tool to discover insights about your usage patterns. With the insights, you can apply cost allocation tags and set up budgets and alerts. That'll help you even more in the optimization process.

  • user123 1 year ago | prev | next

    Curious whether monitoring tools such as CloudWatch or Datadog played a role in detecting issues that led to high memory usage?

    • ops-engineer 1 year ago | next

      @user123 We primarily used CloudWatch, which worked smoothly with our other AWS services. It provided enough information to identify and work on the memory-intensive issues.

  • analytics-enthusiast 1 year ago | prev | next

    Mind sharing details about your auto-scaling policies? That would be interesting to know, and could help those who are trying to scale automatically based on memory usage.

    • scaling-advisor 1 year ago | next

      We've set up scaling policies based on CloudWatch alarms, both on average and maximum memory utilization. In our experience, it's crucial to define alarms with some margin to avoid bouncing between scaling activities.

  • team-lead 1 year ago | prev | next

    @scaling-advisor, that's great advice. Would the team be willing to share some lessons learned or pitfalls to avoid while implementing the scaling policies?

    • scaling-advisor 1 year ago | next

      Of course, a major pitfall we found was not fine-tuning the scaling metrics and thresholds. We had to iterate and adjust them based on our specific application and infrastructure needs to minimize costs and ensure performance consistency.

      • team-lead 1 year ago | next

        Thanks for sharing! We'll keep an eye on fine-tuning scaling metrics and thresholds to ensure optimal scaling policies.

  • outsider 1 year ago | prev | next

    How did you ensure that your infrastructure settings didn't become the bottleneck after optimizing memory management? Very often I've seen this happening in teams, and the performance improves for a while but then goes sour.

    • infrastructure-manager 1 year ago | next

      @outsider, a great question. We ensured that our infrastructure settings were kept up to date by setting up automated maintenance and review cycles, which included auditing, validations and optimizing the infrastructure components for continued performance and reliability.

  • cost-cutter 1 year ago | prev | next

    Impressive work with a 40% reduction in AWS costs. With careful planning and optimization strategies, I've seen teams reduce their AWS costs by up to 65%. Keep innovating and exploring new techniques!

  • cost-engineer 1 year ago | prev | next

    Comprehensive optimization efforts like these can significantly reduce AWS costs. I'd highly recommend the team to investigate the potential of using AWS Savings Plans in the future as well.

  • performance-enthusiast 1 year ago | prev | next

    Excellent job! It'd be interesting to understand if this memory optimization has led to any performance improvements as well. Did you witness any enhancements in responsiveness, reduced latency or improvements in your CI/CD pipeline?