This is the second portion of a two-part series on automated backups and disaster recovery for AWS. In part 1, we summarized the main options: database snapshots, read replicas, and multiple available zones (Multi-AZ) and walked thorugh the simplest solution: backups. Today, we'll setup a read replica and multi-az.
Have you ever lost data? It can make for a bad day.
Now, imagine you lose your customer's data. That can make for a bad week, if you're lucky. If you're not so lucky, it can cost money, customer trust, bad publicity, and much more.
In today's episode we are covering disaster recovery on AWS. In particular, we will be focusing on a few techniques to deal with data loss mitigation and resiliency.
Looking for a fresh, 2018 approach to deploying a Rails app to AWS? We've partnered with DailyDrip on a series of videos to guide you through the process. We're covering how to Dockerize a Rails app, AWS Fargate, logging, monitoring, setting up load balancing, SSL, CDN, and more.
In our previous videos, we dockerized our Rails app, setup an ECS container, deployed to AWS Fargate, configured logging, and monitored our app's performance. However, we still have a few remaining items.
What's left in our AWS production deployment punch list? Configuring a load balancer, SSL, and a CDN. We're using containers, which gives us a great way to scale, but have left out some pretty important pieces to the puzzle.
In today's video, we're going to address these issues. Let's jump in.
It's a lot harder connecting the dots of the request lifecycle when the final response is built from a number of separate microservices.
However, distributed tracing - which connects a transaction trace across microservices - is getting a lot easier. In this short tutorial, I'll show how to add distributed tracing to your Sinatra web apps via OpenTracing, a vendor-neutral tracing API, and Jaeger, an opensource distributed tracing system.
Prior to releasing our Python Performance Monitoring agent, we took a look at the Python ecosystem to see how Scout can compliment the existing landscape. What follows is a summary of our internal report.
The Python ecosystem has a wealth of monitoring tools. That said, making sense of each tool's specialty - and where overlaps exist - is a challenge.
In this post, I hope to give a clear picture of the different monitoring and debugging tools available in the Python world and explain how they fit together.
Looking for a fresh, 2018 approach to deploying a Rails app to AWS? We've partnered with DailyDrip on a series of videos to guide you through the process. We'll be covering how to Dockerize a Rails app, AWS Fargate, logging, monitoring, and CDN support.
Today, we're configuring application performance monitoring for our Rails app using Scout. In the last video, we configured AWS to ship our logs to LogDNA, but logging is just one of the three pillars of observability. With Scout's transaction traces we can easily find performance bottlenecks within our app and database layers.
Let's dive in.