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Calyptia Core Released

Calyptia announced the general availability of Calyptia Core, a Kubernetes solution that simplifies data collection, aggregation and routing at scale.

Calyptia Core removes the operational burden so teams can concentrate on what matters most — discovering actionable insights from their data.

Calyptia Core's plug-and-play approach to configuring data sources and destinations enables users to quickly and easily aggregate observability data at scale and ensures that all data is captured, transformed and routed as desired.

“Until now, observability into Kubernetes clusters has been a very manual, time-consuming and complex process that often delays results. As a business, this leaves you in a position where you tend to focus more on the collection and maintenance of tooling for data management, than extracting value from it,” said Calyptia CEO and Co-founder Eduardo Silva. “Calyptia Core makes it easier to run your business.”

Calyptia Core is available now and integrates with all major backends used for storing and analyzing observability data (Splunk, Datadog, OpenTelemetry, Elasticsearch, S3, etc.). It complements a business’s existing observability analytics, monitoring, and security tools. Other benefits include:

- Reduced cost from using instream processing to route or remove nonessential data to lower-cost storage, ultimately reducing the data stored and processed by expensive search and analytics tools

- Enhanced security by removing the requirement to share secrets and credentials between data sources and destinations

- High-performance scaling that can process petabytes of data across thousands of sources and destinations per day while maintaining low CPU and memory footprints

- Flexible with powerful processing rules for adding information that would otherwise be unavailable further downstream or removing information that should not be stored

Calyptia Core also includes automation of data collection, ability to create custom data pipelines for aggregation that facilitates data processing and filtering, a control plane to provide fine-grained management of the process and extensive developer toolsets to simplify enterprise adoption.

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Calyptia Core Released

Calyptia announced the general availability of Calyptia Core, a Kubernetes solution that simplifies data collection, aggregation and routing at scale.

Calyptia Core removes the operational burden so teams can concentrate on what matters most — discovering actionable insights from their data.

Calyptia Core's plug-and-play approach to configuring data sources and destinations enables users to quickly and easily aggregate observability data at scale and ensures that all data is captured, transformed and routed as desired.

“Until now, observability into Kubernetes clusters has been a very manual, time-consuming and complex process that often delays results. As a business, this leaves you in a position where you tend to focus more on the collection and maintenance of tooling for data management, than extracting value from it,” said Calyptia CEO and Co-founder Eduardo Silva. “Calyptia Core makes it easier to run your business.”

Calyptia Core is available now and integrates with all major backends used for storing and analyzing observability data (Splunk, Datadog, OpenTelemetry, Elasticsearch, S3, etc.). It complements a business’s existing observability analytics, monitoring, and security tools. Other benefits include:

- Reduced cost from using instream processing to route or remove nonessential data to lower-cost storage, ultimately reducing the data stored and processed by expensive search and analytics tools

- Enhanced security by removing the requirement to share secrets and credentials between data sources and destinations

- High-performance scaling that can process petabytes of data across thousands of sources and destinations per day while maintaining low CPU and memory footprints

- Flexible with powerful processing rules for adding information that would otherwise be unavailable further downstream or removing information that should not be stored

Calyptia Core also includes automation of data collection, ability to create custom data pipelines for aggregation that facilitates data processing and filtering, a control plane to provide fine-grained management of the process and extensive developer toolsets to simplify enterprise adoption.

The Latest

In MEAN TIME TO INSIGHT Episode 14, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud network observability... 

While companies adopt AI at a record pace, they also face the challenge of finding a smart and scalable way to manage its rapidly growing costs. This requires balancing the massive possibilities inherent in AI with the need to control cloud costs, aim for long-term profitability and optimize spending ...

Telecommunications is expanding at an unprecedented pace ... But progress brings complexity. As WanAware's 2025 Telecom Observability Benchmark Report reveals, many operators are discovering that modernization requires more than physical build outs and CapEx — it also demands the tools and insights to manage, secure, and optimize this fast-growing infrastructure in real time ...

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...