[Hawkular-dev] Hawkular Metrics - Roadmap

[mike thompson]

I didn’t see any mention of streaming metrics. I know this is something that we had discussed. Since we already have observables in Metrics, opening up a web socket  and streaming the metrics updates seems like a natural fit and capability that few solutions currently have to offer.
Also, providing an Rx.js consumer on the hawkular charts side would allows to chart in real-time metrics with minimal bandwidth (especially with dashboards and NOCs)


> On 15 Mar 2016, at 13:00, Stefan Negrea <snegrea at redhat.com> wrote:
> 
> Hello Everybody,
> 
> Hawkular Metrics contributors have been working for the past few weeks on a roadmap for the upcoming year. The goal is to give clarity on the project direction, serve as a planning tool for releases, and show our strong commitment to open source.
> 
> The project and community are enjoying excellent growth. A maturing code base, an ever growing set of integrations, and consistent community contributions are ingredients that make this project successful and also an indication of the future.
> 
> For those not familiar with Hawkular Metrics, the project is a high performance and high availability storage engine for large volume metric data. The project uses Cassandra as a storage engine because of its flexible data model well suited for time-series data storage and linear scalability with no single point of failure.
> 
> 
> Here is the roadmap:
> 
> 1) Cassandra 3.x
>  * The 3.x release of Cassandra is maturing, making the perfect timing for the project to transition from current 2.2.x line
>  * Expect this transition to happen rather soon since work is already in progress (driver updates, and a schema management tool)
> 
> 2) Pre-computed aggregates
>  * Needed to support long term data storage and retrieval for high volume metrics
>  * Single metrics roll-ups are also the foundation for pre-computed multi-metric aggregations, that goal is to work on this subsequent to single metric roll-ups
> 
> 3) Metric Enhancements
>  * Histogram metrics are fairly common in other time series databases. The plan is to add histogram metrics as a sub-metric to existing gauge metrics, analogous to what counter-rate metrics are counter metrics. It is common to do the calculations need for the histogram on the client side, but there are a lot of advantages to push the calculations to the server.
>  * Add support for metrics baselines; automatically computed server-side and stored
>  * Implement an Apdex score, similar purpose to baselines, but based on the open standard
> 
> 4) Native Grafana integration
>  * Grafana integration is important for Hawkular Metrics due to lack of a dedicated UI. Currently Grafana integration works through an InfluxDB compatibility layer that has obvious disadvantages (maintaining compatibility with InfluxDB, limited set of features based on the InfluxDB capability). 
>  * A native Grafana provider will be easier to maintain and expose the full feature set of Hawkular Metrics
> 
> 5) Developer Support
>  * Provide a Hawkular Metrics distribution with all components needed for third-party developers to get a developer environment running with minimal effort
>  * An easy-to-use and all-inclusive distribution will avoid having platform developers configure Wildfly server and a Casasndra cluster just to test or write integration code
> 
> 6) Import & Export Data APIs
>  * The project already provides a growing set of APIs for querying metric data, but there are scenarios that require bulk data export into another system for further analysis. And vice-versa, import large amounts of data from another system for longer term storage and aggregation by Hawkular Metrics.
>  * The goal is to provide APIs optimized for bulk importing or exporting data. Tools need to be both fast and easy to use, with the primary use case of moving a large amounts data well beyond the capability of current REST interface (eg. moving 100GB of data).
> 
> 7) ElasticSearch integration
>  * An optional integration with Elastic Search for tasks beyond the capability of Cassandra. 
>  * Basic examples for this are whole tenant searches and aggregation of text based data, such as tags, events, and even availability.
> 
> 
> If you have any other suggestion or would like to contribute to the project, please contact me; feedback is more than welcomed.
> 
> 
> Thank you,
> Stefan Negrea
> 
> Software Engineer
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