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Thundra Achieves AWS Lambda Ready Designation

Thundra achieved the AWS Lambda Ready designation, part of the Amazon Web Services (AWS) Service Ready Program.

This designation recognizes that Thundra has demonstrated successful integration with AWS Lambda from observability, debugging, and security aspects.

Achieving the AWS Lambda Ready designation differentiates Thundra as an AWS Partner Network (APN) member with a product integrating AWS Lambda, and is generally available and fully supported for AWS customers. AWS Service Ready Partners have demonstrated success in building products integrated with AWS services, helping AWS customers evaluate and use their technology productively at scale and varying levels of complexity.

"Our team is dedicated to helping companies innovate with AWS Lambda quickly, safely, and efficiently by increasing developer productivity and thus the agility to respond to issues. Thundra is proud to achieve AWS Service Ready Status as a recognition of our dedication," says Emrah Samdan, VP of Products for Thundra.

To support seamless integration and deployment of AWS Lambda and other solutions, AWS established the AWS Service Ready Program to help customers identify products integrated with AWS services, and spend less time evaluating new tools and more time scaling their use of products that are integrated with AWS Services.

Thundra provides deep security and performance insights into serverless workloads architected on AWS Lambda. Developer productivity is boosted by Thundra's online and offline debugger, which allows developers to debug AWS Lambda functions on common IDEs such as Microsoft Visual Studio Code and IntelliJ IDEA. Thundra's distributed tracing approach is designed to provide end-to-end visibility for event-driven architectures using asynchronous communication. Thundra replaces multiple tools that organizations are typically using, providing application teams with insights, recommendations, and actions to efficiently identify issues and opportunities for improvements, troubleshooting and debugging, enforcing application security and compliance, and maintaining availability, performance, and cost SLAs. Since its inception, Thundra has been helping many customers to run efficient and reliable applications on AWS Lambda.

"Thundra is now a must-have in our toolkit when building serverless applications with AWS Lambda. It's a clear improvement on other similar products and gives us the insight that we need to keep things running smoothly for our customers and clients," says Aaron Jensen, Principal Developer at Substantial.

In these unprecedented times due to the COVID-19 pandemic, Thundra supports non-profit and health organizations by providing Thundra for free at any scale and by donating 1% of its monthly revenue to the COVID-19 Solidarity Response Fund initiated by the World Health Organization.

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Thundra Achieves AWS Lambda Ready Designation

Thundra achieved the AWS Lambda Ready designation, part of the Amazon Web Services (AWS) Service Ready Program.

This designation recognizes that Thundra has demonstrated successful integration with AWS Lambda from observability, debugging, and security aspects.

Achieving the AWS Lambda Ready designation differentiates Thundra as an AWS Partner Network (APN) member with a product integrating AWS Lambda, and is generally available and fully supported for AWS customers. AWS Service Ready Partners have demonstrated success in building products integrated with AWS services, helping AWS customers evaluate and use their technology productively at scale and varying levels of complexity.

"Our team is dedicated to helping companies innovate with AWS Lambda quickly, safely, and efficiently by increasing developer productivity and thus the agility to respond to issues. Thundra is proud to achieve AWS Service Ready Status as a recognition of our dedication," says Emrah Samdan, VP of Products for Thundra.

To support seamless integration and deployment of AWS Lambda and other solutions, AWS established the AWS Service Ready Program to help customers identify products integrated with AWS services, and spend less time evaluating new tools and more time scaling their use of products that are integrated with AWS Services.

Thundra provides deep security and performance insights into serverless workloads architected on AWS Lambda. Developer productivity is boosted by Thundra's online and offline debugger, which allows developers to debug AWS Lambda functions on common IDEs such as Microsoft Visual Studio Code and IntelliJ IDEA. Thundra's distributed tracing approach is designed to provide end-to-end visibility for event-driven architectures using asynchronous communication. Thundra replaces multiple tools that organizations are typically using, providing application teams with insights, recommendations, and actions to efficiently identify issues and opportunities for improvements, troubleshooting and debugging, enforcing application security and compliance, and maintaining availability, performance, and cost SLAs. Since its inception, Thundra has been helping many customers to run efficient and reliable applications on AWS Lambda.

"Thundra is now a must-have in our toolkit when building serverless applications with AWS Lambda. It's a clear improvement on other similar products and gives us the insight that we need to keep things running smoothly for our customers and clients," says Aaron Jensen, Principal Developer at Substantial.

In these unprecedented times due to the COVID-19 pandemic, Thundra supports non-profit and health organizations by providing Thundra for free at any scale and by donating 1% of its monthly revenue to the COVID-19 Solidarity Response Fund initiated by the World Health Organization.

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In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...