Currently, the world generates an unprecedented amount of data. Research shows that the world generated more data in the last two years than the amount of data produced in the history of the human race. The most critical part of this entails analyzing the generated data and observing trends. It's at this point where tools like Scout APM, Datadog, and AppDynamics become crucial. Working with an unprecedented amount of data means tackling millions/thousands of distinct data points.

Can you imagine trying to keep track of all your prospect- and customer-related activities on a spreadsheet? What about ye olde days of rolodexes (do people still remember what those are?!)? Thank goodness for Salesforce, the Customer Relationship Management (CRM) solution that revolutionized sales, marketing, and customer care - and how we interact with customers in general. Salesforce is a critical component for many businesses.

What will the future of observability look like? Four core capabilities will be foundational to the next generation of solutions.

We are proud to announce the preview release of the Elastic APM iOS agent! This release is intended to elicit feedback from the community, while providing some initial functionality within the Elastic Observability stack and is not intended for production use. Now is your chance to influence the direction of this new iOS agent and let us know what you think on our discussion forum. If you find an issue, or would like to contribute yourself, visit the GitHub repository.

To realize the full potential of APM, many customers are migrating from their existing APM 10.7 clusters to DX APM. In addition, they continue to onboard new applications for monitoring. These efforts require a series of steps, including the configuration of experience views, universes, and DX Operational Intelligence services.

Jaeger is a popular open-source tool used for distributed tracing in a microservice architecture. In a microservice architecture, a user request or transaction can travel across hundreds of services before serving what a user wants. Distributed tracing helps to track the performance of a transaction across multiple services. Before we deep dive into how Jaeger accomplishes distributed tracing for microservices-based architecture, let's take a short detour to understand distributed tracing.

Exciting key changes to our Global Partner Program will help our partners fully exploit the potential of full-stack observability with business context.

We're excited to help our customers further leverage the benefits of OpenTelemetry via integration with AWS Distro for OpenTelemetry (ADOT) for traces 1.0.

In the realm of monitoring products, proactive monitoring usually means identifying potential issues within IT infrastructure and applications before users notice and complain and initiating actions to avoid the issue from becoming user noticeable and business impacting. Proactive monitoring means a business is continuously searching for signs that indicate a problem is about to happen.

The current big data world allows even tiny IT environments to produce massive amounts of information. After determining how to open up various data generation sources, a business analyzes the information. Here, the analysis method you leverage varies depending on the data, the tools/equipment used, and the use case. A good practice is to visualize the traces, weather logs, data, or metrics.

We chatted with top IT leadership about the impact that full-stack observability has on their business. Here’s what they had to say.

Both DataDog and Jaeger are tools used to monitor application performance. The difference lies in what they monitor and terms of usage. Jaeger is an open-source tool focused on distributed tracing of requests in a microservice architecture. While DataDog is a SaaS APM vendor covering most monitoring needs of an application. Application performance monitoring is the process of keeping your app's health in check. APM tools enable you to be proactive about meeting the demands of your customers.

Both AWS X-Ray and Jaeger are distributed tracing tools used for performance monitoring in a microservices architecture. Jaeger was originally built by teams at Uber and then open-sourced in 2015. On the other hand, AWS X-Ray is a distributed tracing tool provided by AWS specifically focused on distributed tracing for applications using Amazon Cloud Services. Jaeger is a popular open-source tool that graduated as a project from Cloud Native Computing Foundation.

Application performance monitoring (APM) is important for the development of any web app. But monitoring software is not an easy process; you have to observe various metrics and be calculative in observing measurements like the application’s speed, error percentage, memory bloat, number of API calls per day, and much more.

In software terms, “open source” means applications and their source code are available for the public to download and modify free of cost. Anyone can access, edit, and supplement the code to create an enhanced version of the application. Vendors often do this by forking the source code to create their own version of the application, marketing their version commercially.

It is incumbent on cloud operations teams to choose the correct type of AWS EC2 instance relative to the underlying application. The wrong choice could adversely impact business and user experience. This article walks through a customer case study where the EC2 instance choice impacted their business.

Distributed tracing is becoming a critical component of any application's performance monitoring stack. Setting it up in-house is a hearculean task, and that's why many companies prefer outside tools. Jaeger and Zipkin are two popular open-source projects used for end-to-end distributed tracing. Let us explore their key differences in this article.

Jaeger is an open-source end-to-end distributed tracing tool for microservices architecture. On the other hand, Elastic APM is an application performance monitoring system that is built on top of the ELK Stack (Elasticsearch, Logstash, Kibana, Beats). In this article, let's explore their key features, differences, and alternatives. Application performance monitoring is the process of keeping your app's health in check. APM tools enable you to be proactive about meeting the demands of your customers.

Managing containers effectively in multi-cloud environments is nearly impossible. Kubernetes makes it possible.

Jaeger and New Relic are tools used in the application monitoring and observability domain. While Jaeger is an open source tool under Cloud Native Computing Foundation, New Relic is a SaaS vendor in the observability domain. Let us explore the key differences between Jaeger and New Relic in this article. New Relic is an extensive SaaS tool and provides application performance as well as infrastructure monitoring. Jaeger provides an open-source solution for end-to-end distributed tracing.

Jaeger and OpenTracing are both open-source projects. Jaeger was originally built by teams at Uber and then open-sourced. The OpenTracing project was also started by teams at Uber, and hence they are compatible with each other. While Jaeger is an end-to-end distributed tracing tool, OpenTracing is a set of APIs and libraries that can be used to instrument your application.

Dynatrace is a publicly-traded global technology company that provides a software intelligence platform based on artificial intelligence (AI) and automation to monitor and enhance application performance, development and security, IT infrastructure, and user experience for enterprises and government organizations around the world. The headquarters of Dynatrace is in Waltham, Massachusetts. Dynatrace's CEO is John Van Siclen.

Folks! Great to have you over for our monthly product update aka Signal #04. This month we made great strides in both our frontend and backend pods. Metrics ingestion, testing frameworks, improved tracking features for gRPC calls and much more! We also crossed 200+ members on our slack community 🎉🎉🎉 Let's dive in to see what humans at SigNoz have been upto!

Infrastructure as code and automating deployment and scale-up/down in Azure is becoming the new normal. Solution architects and system administrators are becoming coders and scripting is becoming part of their day-to-day job, whilst in parallel a raft of vendors is providing products to try and help avoid this need to script and address the shortage of staff with those skills to script and code this now necessary functionality.

Choosing the perfect Application Performance Monitoring tool for your business always remains a tricky decision. There are so many options in the market, and each alternative has its own set of features and flaws. Sometimes, the profile of two solutions overlaps, which creates an even bigger grey area around which to opt.

Seamlessly visualize AppDynamics data and powerful application insights alongside your other data sources in Amazon Managed Grafana with our new plug-in.