Category: Monitoring and observability

In this post, delve into the process of detecting tenant activities within microservices spanning multiple AWS accounts. We provide insights into instrumenting AWS Lambda functions to include tenant information in tracing using ADOT and demonstrated how to establish a service map across several AWS accounts using Amazon CloudWatch. By leveraging AWS observability technology, SaaS providers can enhance operational efficiency and redirect their attention towards their desired development goals.

By automating performance testing and including chaos testing, organizations can identify failure scenarios in systems before they develop and cause downtime. Learn how Distributed Load Testing on AWS (DLT) automates performance testing at scale, and how AWS Fault Injection Simulator (AWS FIS) performs controlled chaos engineering experiments on AWS resources. By combining the power of AWS FIS and DLT, organizations can perform comprehensive resilience testing and continuously validate their systems.

With the rise of large language models, natural language processing, and generative AI models, embeddings are becoming a critical piece of data in more machine learning use cases. In this post, explore different ways embeddings are used in machine learning and where problems can show up that impact your ML models, and how you can use WhyLabs to identify those problems and create monitors to avoid them showing up again in the future.

Customers can use Grafana Cloud to connect over 60 of the most popular AWS services. Interacting with those services in Grafana Cloud is easier than ever, providing one portal to set up and manage an entire AWS observability strategy. This post takes a closer look at the changes that will make it easier to manage your AWS environment. Grafana Labs supports users’ infrastructure and applications wherever they are, regardless of data type or source.

The term “API economy” refers to businesses delivering digital services to end users, other company services, or partners. This post discusses the necessary aspects to achieve an observability model in the API economy, including a practice example with an architecture design and related technologies. Based on Pragma’s extensive experience, explore the mainstays of observability and the importance of having well-defined observability architecture to have a thriving API economy model at scale.

Monitoring containerized applications can be challenging due to the isolated environment that containers provide. A comprehensive monitoring strategy is essential, including how to choose tools to collect and analyze resource usage, network traffic, and application logs. Learn how eCloudvalley leverages AWS Distro for OpenTelemetry to help customers centralize their monitoring in Amazon CloudWatch for their Amazon EKS environment.

Many companies report the biggest challenge when adopting Kubernetes is a lack of in-house skills. Infrastructure as code (IaC) blueprints can mitigate these gaps by accelerating hands-on experience, providing a reproducible foundation to configure, provision, and destroy clusters easily. Learn how Sysdig launched an add-on for Amazon EKS as well as Sysdig EKS Blueprints to enable organizations to confidently deploy instrumented Kubernetes clusters using Terraform.

As companies adopt a cloud-first strategy, ITOps and DevOps require a single view of application services and infrastructure so they can be equipped with the right observability solution. Observability lets you determine what’s important by watching how the system performs over time, and ask new questions using metrics, logs, or traces. Tech Mahindra’s smart monitoring and resolution tool is called SMART and is built on top of AWS observability and telemetry tools.

Voice services play a significant role across many industries by enabling real-time and critical communications; but building the computing infrastructure internally to deliver a high-quality voice service involves considerable capital and operational expenses. This post discusses the current challenges in monitoring voice call quality and how Voipfuture’s Qrystal for AWS can be used to bring enriched visibility into your critical communication infrastructure.