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The latest News and Information on Monitoring for Websites, Applications, APIs, Infrastructure, and other technologies.

Monitor Sidekiq with Datadog

Sidekiq is a Ruby framework for background job processing. Developers can use Sidekiq to asynchronously run computationally intensive tasks—such as bulk email sending, payment processing, and data importing—to help speed up the response times of their applications. If you’re using Sidekiq Pro or Enterprise, Datadog’s integration helps you monitor the progress of your jobs and the applications that depend on them, all in a single platform.

Monitor Windows containers on Google Cloud with Datadog

Many organizations already use Docker to containerize their Windows applications and often run mixed Windows and Linux container environments to support complex architectures. With Kubernetes’s support for deploying clusters with Windows nodes, organizations can leverage the orchestration platform to easily automate container provisioning, networking, scaling, and more for their Windows applications.

Improving Graphite rollup and runtime consolidation in Metrictank and Grafana 7.0 with lineage metadata

The Grafana and Metrictank/Graphite teams have been hard at work to deliver an exciting new feature for the upcoming Grafana v7.0 release: a rollup indicator and series lineage metadata breakdown for Metrictank. This blog will cover the new functionality around Metrictank metadata, the rollup indicator, and the lineage visualization coming in 7.0.

Log management: The key to centralized log aggregation and easy troubleshooting

A large number of security breaches are impacting industry verticals, including banking, financial services and insurance (BFSI), telecom, and hospitality, so there's a growing need for organizations to fortify their infrastructure against these threats. For example, by the time T-Mobile identified the intrusion and unauthorized access to its sensitive data in 2019, both its customer and employee details were already stolen by hackers.

Identifying EC2 Right Sizing Opportunities for Cost Optimization | Datadog Tips & Tricks

In this video, you’ll learn how to identify right sizing opportunities for your EC2 instances utilizing Datadog metric dashboards. Optimizing your cloud footprint for cost efficiency can be a huge task, especially for large and scaling environments. Utilizing time series data and toplists, Datadog dashboards allow you to see chronically underutilized EC2s in your AWS environment. Template variables allow you to sort EC2s by teams and instance types, so you quickly identify the scope of cost saving opportunities across your organization.

Tip of the Day - Effective DEM

A truly comprehensive Digital Experience Monitoring strategy requires monitoring from the perspective of the end user with an outside-in approach. Solutions that claim to offer DEM often use nodes placed in cloud providers to conduct synthetic monitoring tests, which doesn't emulate the flow of traffic from actual users. Learn how Catchpoint's DEM platform provides true observability data that ensures availability, reachability, performance, and reliability through proactive synthetic and real user monitoring.

The Expensive History of APM

When done well, application performance monitoring (APM) is a magical and irreplaceable tool. However, over the years, enterprises have sometimes paid dearly to implement it. APM’s task seems simple enough—replace emotional user anecdotes about application performance with quantifiable, actionable data. But the devil can certainly be in the details with APM.

Page Load Time vs. Response Time - What Is the Difference?

Page load time and response time are key metrics to monitor, and they can give you an in-depth understanding of how your website is performing. However, the difference between page load time and response time isn’t immediately obvious, and neither are the benefits of tracking them independently.

5 Benefits of Cloud-Based Log Aggregation Tools

In the modern digital ecosystem, every user activity, system error, application transaction, and network packet movement can be tracked using logs. This level of visibility into systems, networks, and applications is useful for troubleshooting bottlenecks, analyzing past trends, and predicting future events. However, monitoring various cloud-based and on-premises resources becomes complex in the absence of proper log aggregation tools.

Can AWS API Gateway Act as a Load Balancer?

TL;DR: yes, API Gateway can replace what a Load Balancer would usually provide, with a simpler interface and many more features on top of it. The downside is that it doesn’t come cheap. Load balancers have been one of the most common ways to expose a backend API to the public or even to an internal/private audience. API Gateways seem to provide the same functionality: map and connect HTTP requests to a backend service. So, are they the same or are there any differences?