Last month we announced the beta for IRONdb and launched the Circonus time series database as a new standalone product for the Graphite ecosystem. Now IRONdb is publically available for installation. You can read more about it in the press release, or visit the homepage devoted to IRONdb on our website.
IRONdb enhances Graphite, enabling data replication, easier maintenance with seamless upgrades, and the scalability to handle millions of metrics. You can explore IRONdb plugins on Github with Circonus Labs here and here, or get the details in our Technical Manual. You can also visit the Circonus Labs Slack community and ask about it in the #irondb channel.
Anyone using Graphite or Grafana would stand to benefit immensely from adding IRONdb to their infrastructure, and should sign up for an installation today!
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IRONdb is a replacement for Whisper and Carbon-cache in Graphite that’s faster, more efficient, and easier to operate and scale. Circonus developed IRONdb by adding extensions to support the Graphite data format on ingestion and interoperability with Graphite-web and Grafana to Circonus’s existing internally developed time series database.
IRONdb is a drop-in solution for organizations struggling to scale Graphite or frustrated with maintaining a high availability metrics infrastructure during surges and outages and even routine maintenance. Highly scalable and robust, IRONdb has support for replication and clustering for redundancy of data, is multi-data center capable, and comes with a full suite of administration tools.
Introducing IRONdb in his latest blog post, Circonus VP of Engineering, Riley Berton, dives into greater detail about how IRONdb achieves these key features.
DID YOU KNOW?
The more data you can store, the more accurate and powerful your analysis. How many Graphite users run a time series database with 1 million metrics? A few. 10 million metrics? Honestly, just one or two we know of. 50 million metrics? No one. Why? Because it couldn’t be done, before now. What if you could access a scalable time series database to handle high-volume, high-frequency data and have that data be highly available? You could do so much more with your data. Last month, Riley Berton gave a talk at Grafanacon 2016 about the IRONdb beta. Now the video from that conference is available.