Catchpoint®, announced the acquisition of the assets of Thundra.io, a pioneer in cloud monitoring, a move that strengthens Catchpoint’s Application Experience Solution with advanced microservices and API monitoring capabilities, both critical aspects of Internet Performance Monitoring (IPM).
Today’s applications are increasingly complex, distributed, and often dependent on third-party services accessed through APIs. Whether multi-cloud, serverless, or third-party, these application services must be reachable, performant, and reliable. Ensuring the availability and performance of cloud functions, microservices, and APIs is often critical to the operation of applications, systems, or even the business. Modern organizations need to build a competency around them in their quest to achieve Internet Resilience.
“API monitoring is becoming increasingly important for our customers, and many of them plan to invest in API, cloud functions, and microservices monitoring this year,” said Mehdi Daoudi, Chief Executive Officer, and co-founder of Catchpoint. “Incorporating Thundra.io’s powerful technology into Catchpoint’s IPM platform will propel us forward to deliver the important capabilities our customers need for today and the future.”
Today, Catchpoint provides API monitoring for critical applications, from manufacturing facilities to the APIs consumed by mobile devices and third-party services. The acquisition will enable Catchpoint to incorporate advanced technologies into the IPM platform in the coming months to offer what could be the most advanced cloud API monitoring capabilities in the market.
Thundra.io is well known for its serverless performance monitoring, real-time debugging, and their specific capabilities to optimize Lambda functions. These capabilities help DevOps teams achieve resiliency for modern, internet-native applications, ensuring their performance and reliability in the modern applications landscape.
Some of the existing capabilities Catchpoint plans to integrate into the IPM platform include:
- Lightweight, on-demand, proactive monitoring for modern internet-based applications
- Automatic discovery and mapping of serverless architecture
- Visual transaction diagram with latency issues and errors, function flow, and call tracing
- Support for modern technologies including Lambda, Node.js, Python, Java, Go, and .net
- Support for Open Telemetry data formats
As part of the acquisition, the existing Thundra.io team has joined Catchpoint and will be located at a newly established center of excellence in Ankara, Turkey. The team will integrate and enhance the serverless and microservices monitoring capabilities within Catchpoint’s leading IPM platform. The team will also help accelerate the adoption of Open Telemetry in the IPM platform.
The combination of advanced microservices and API monitoring with the rest of the capabilities in the Internet Performance Monitoring platform provides IT teams with the most complete view of the Internet stack, enabling them to catch incidents before they become outages, and helping organizations achieve Internet Resilience.
The Latest
In MEAN TIME TO INSIGHT Episode 6, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network automation ...
In the ever-evolving landscape of software development and infrastructure management, observability stands as a crucial pillar. Among its fundamental components lies log collection ... However, traditional methods of log collection have faced challenges, especially in high-volume and dynamic environments. Enter eBPF, a groundbreaking technology ...
Businesses are dazzled by the promise of generative AI, as it touts the capability to increase productivity and efficiency, cut costs, and provide competitive advantages. With more and more generative AI options available today, businesses are now investigating how to convert the AI promise into profit. One way businesses are looking to do this is by using AI to improve personalized customer engagement ...
In the fast-evolving realm of cloud computing, where innovation collides with fiscal responsibility, the Flexera 2024 State of the Cloud Report illuminates the challenges and triumphs shaping the digital landscape ... At the forefront of this year's findings is the resounding chorus of organizations grappling with cloud costs ...
Government agencies are transforming to improve the digital experience for employees and citizens, allowing them to achieve key goals, including unleashing staff productivity, recruiting and retaining talent in the public sector, and delivering on the mission, according to the Global Digital Employee Experience (DEX) Survey from Riverbed ...
App sprawl has been a concern for technologists for some time, but it has never presented such a challenge as now. As organizations move to implement generative AI into their applications, it's only going to become more complex ... Observability is a necessary component for understanding the vast amounts of complex data within AI-infused applications, and it must be the centerpiece of an app- and data-centric strategy to truly manage app sprawl ...
Fundamentally, investments in digital transformation — often an amorphous budget category for enterprises — have not yielded their anticipated productivity and value ... In the wake of the tsunami of money thrown at digital transformation, most businesses don't actually know what technology they've acquired, or the extent of it, and how it's being used, which is directly tied to how people do their jobs. Now, AI transformation represents the biggest change management challenge organizations will face in the next one to two years ...
As businesses focus more and more on uncovering new ways to unlock the value of their data, generative AI (GenAI) is presenting some new opportunities to do so, particularly when it comes to data management and how organizations collect, process, analyze, and derive insights from their assets. In the near future, I expect to see six key ways in which GenAI will reshape our current data management landscape ...
The rise of AI is ushering in a new disrupt-or-die era. "Data-ready enterprises that connect and unify broad structured and unstructured data sets into an intelligent data infrastructure are best positioned to win in the age of AI ...
A majority (61%) of organizations are forced to evolve or rethink their data and analytics (D&A) operating model because of the impact of disruptive artificial intelligence (AI) technologies, according to a new Gartner survey ...
