Advent at Grakn Labs: Cloud/DevOps

#GraknLovesTech: 6th December 2016

Thanh Pham
Dec 6, 2016 · 4 min read
By Juandev (Own work) [CC BY-SA 3.0 (], via Wikimedia Commons

Here at Grakn Labs we love technology. So much so, that, this month, we’ve decided to share our favourite technology moments from 2016. Each weekday during December, we will open a window on our virtual advent calendar, and peek inside to recall some of the greatest innovation or news that the past year has brought us.

Please recommend and share with hashtag #GraknLovesTech if you enjoy our posts. And if you have any favourite links you’d like us share, just leave us a comment or tweet us @graknlabs!

Today we are featuring the year’s most interesting breakthroughs in Cloud Technology and DevOps, which have had a big year, as they have increasingly gained enterprise recognition.

DevOps in Enterprises

An integral consideration for large organizations when choosing to adopt new technologies and practices is always security. Indeed, the past year has seen a big rise in DevSecOps and securing containers — according to the Puppet State of DevOps report security should be integrated into the daily workflow and automated testing processes.

“Why we fail at scale” — Joanne Molesky

Joanne Molesky from Thoughtworks gave a talk at DevOps Days London on why enterprises fail to adopt DevOps and gave inspiring examples of when they overcame those struggles:

  • Etsy and PCI-DSS
  • UK’s Government Digital Services
  • Suncorp Group Limited

The highlight of the talk was that current technology enables us to deliver products faster than ever, and that old fashioned business processes are the bottleneck. An organisation needs to embrace changes to its business practices first, before it can change its technology infrastructure. One interesting case study was that of Suncorp. They had their legal and risk/compliance staff join weekly standups as part of the “simplification” programme, aimed at reducing the number and complexity of legacy systems and business processes.

If you can’t change the process (PCI DSS), don’t follow traditional solutions; understand what the goal is and minimise the impact on the product delivery.

New age monitoring

Set against Nagios, Prometheus has integrated modern graphing tools, coupled with flexible querying. This allows you to create ad hoc graphs and tables to compare metrics and track down performance anomalies in the system with greater ease. I remember having numerous tabs open when working with Nagios and that was quite painful. Check out the live demo of Prometheus from Robust Perception.

Also often put on the same shelf as Graphite/InfluxDB/OpenTSDB, Prometheus is a full monitoring solution that includes alerting, not just a passive time series store with graphing. It is also more straightforward to set up as everything is in one package with a range of metrics exporters.

This year, the project resurfaced for two reasons:

This should mean a lot more traction and I’m excited to see what comes next!

“Prometheus: A Next Generation Monitoring System (FOSDEM 2016)” — Brian Brazil

Kubernetes and stateful apps

In terms of features, all container management systems offer roughly the same or will catch up with each other soon. But Kubernetes has one thing that’s difficult to acquire: a community. There is a vast number of official examples, documentation, blog posts and talks showcasing Kubernetes. If you’re trying to run something in k8s, someone has most likely tried that already and blogged about it.

K8s is now one step closer to fully supporting stateful apps with a new feature called Pet Sets. I look forward to being able to take advantage of Kubernetes’s features to scale Cassandra!

“Configuring and Deploying Stateful Applications with PetSet” — Clayton Coleman

Finally, our favourite comedy piece goes to this tube map you can use to find your way to DevOps from where you are right now:

Source: Deloitte

Or click here for its full glory.

Good luck!

GRAKN.AI is an open-source knowledge graph data platform that brings knowledge ontologies and transactional data together to enable highly intelligent querying of data. Querying is performed through Graql, a declarative, knowledge-oriented graph query language for retrieving explicitly stored and implicitly derived information, and for performing graph analytics and automated reasoning. Grakn and Graql will help you effectively manage and harness large-scale graph data by allowing you to model it expressively, migrate it efficiently, and to draw insightful knowledge from your deep information network.

Find out more about Grakn Labs from our website!


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