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OpsDataStore 1.0 Released

OpsDataStore announced the general availability of OpsDataStore 1.0 — a big data back end for all IT management data.

“IT Ops is always looking for a simple and cost effective way to get to the root cause of the problem,” said Larry Dragich, Director of Customer Experience Management at The Auto Club Group. “We have quite a few tools, and OpsDataStore looks like a promising approach to take Enterprise Monitoring to the next level.”

Key features in the OpsDataStore solution include:

- Open Data Collection Architecture – OpsDataStore can consume management data from any platform and any management software product. The solution includes connectors for the VMware vSphere data center virtualization platform, Dynatrace APM, AppDynamics and the ExtraHop wire data platform. In addition to OpsDataStore, third party service providers, management software vendors and customers can quickly add new connectors.

- Dynamic Object Model – Unlike simple metrics stores or log databases, OpsDataStore relates items to each other at ingest time and maintains a continuously updated topology map of the entire environment over time. Any object (transaction, application, virtual server, physical server, datastore, etc.) can be queried for its end-to-end topology at any point in time. The model is continuously and automatically updated, eliminating the need for periodic discovery. The model is also extensible by ecosystem partners and customers for additional objects.

- Real-Time, Highly Scalable Big Data Back End – OpsDataStore is built on state of the art open source, low latency, and big data technologies, including Cassandra (time series database), Spark (stream processing engine), and Kafka (message bus). These technologies enable OpsDataStore to scale to any size environment and process large amounts of data in real time.

- Open Query Architecture – OpsDataStore supports both a REST API and ODBC as an API for data access. Related objects, topologies and metrics in OpsDataStore can be easily consumed by any management software application or custom initiative on the part of any customer.

- Support for Leading BI Tools – The OpsDataStore dashboards are implemented in QlikView and Tableau, two industry standard tools for visualizing data. This makes it easy for IT Operations to publish IT and applications data to constituents that need access to this information.

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OpsDataStore 1.0 Released

OpsDataStore announced the general availability of OpsDataStore 1.0 — a big data back end for all IT management data.

“IT Ops is always looking for a simple and cost effective way to get to the root cause of the problem,” said Larry Dragich, Director of Customer Experience Management at The Auto Club Group. “We have quite a few tools, and OpsDataStore looks like a promising approach to take Enterprise Monitoring to the next level.”

Key features in the OpsDataStore solution include:

- Open Data Collection Architecture – OpsDataStore can consume management data from any platform and any management software product. The solution includes connectors for the VMware vSphere data center virtualization platform, Dynatrace APM, AppDynamics and the ExtraHop wire data platform. In addition to OpsDataStore, third party service providers, management software vendors and customers can quickly add new connectors.

- Dynamic Object Model – Unlike simple metrics stores or log databases, OpsDataStore relates items to each other at ingest time and maintains a continuously updated topology map of the entire environment over time. Any object (transaction, application, virtual server, physical server, datastore, etc.) can be queried for its end-to-end topology at any point in time. The model is continuously and automatically updated, eliminating the need for periodic discovery. The model is also extensible by ecosystem partners and customers for additional objects.

- Real-Time, Highly Scalable Big Data Back End – OpsDataStore is built on state of the art open source, low latency, and big data technologies, including Cassandra (time series database), Spark (stream processing engine), and Kafka (message bus). These technologies enable OpsDataStore to scale to any size environment and process large amounts of data in real time.

- Open Query Architecture – OpsDataStore supports both a REST API and ODBC as an API for data access. Related objects, topologies and metrics in OpsDataStore can be easily consumed by any management software application or custom initiative on the part of any customer.

- Support for Leading BI Tools – The OpsDataStore dashboards are implemented in QlikView and Tableau, two industry standard tools for visualizing data. This makes it easy for IT Operations to publish IT and applications data to constituents that need access to this information.

The Latest

For many B2B and B2C enterprise brands, technology isn't a core strength. Relying on overly complex architectures (like those that follow a pure MACH doctrine) has been flagged by industry leaders as a source of operational slowdown, creating bottlenecks that limit agility in volatile market conditions ...

FinOps champions crucial cross-departmental collaboration, uniting business, finance, technology and engineering leaders to demystify cloud expenses. Yet, too often, critical cost issues are softened into mere "recommendations" or "insights" — easy to ignore. But what if we adopted security's battle-tested strategy and reframed these as the urgent risks they truly are, demanding immediate action? ...

Two in three IT professionals now cite growing complexity as their top challenge — an urgent signal that the modernization curve may be getting too steep, according to the Rising to the Challenge survey from Checkmk ...

While IT leaders are becoming more comfortable and adept at balancing workloads across on-premises, colocation data centers and the public cloud, there's a key component missing: connectivity, according to the 2025 State of the Data Center Report from CoreSite ...

A perfect storm is brewing in cybersecurity — certificate lifespans shrinking to just 47 days while quantum computing threatens today's encryption. Organizations must embrace ephemeral trust and crypto-agility to survive this dual challenge ...

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 ...