From the outset, BigData Boutique brought expertise in areas unknown to Buzzilla, providing an effective and critical consultancy offering. During the selection process, BigData Boutique were always able to answer questions quickly, demonstrating not only their knowledge of Elasticsearch and cloud migration projects, but also their eligibility as an in-house partner.
This, Lior emphasises, made BigData Boutique’s offering superior to other tech firms. There was no doubt in the minds of Buzzilla’s lead developer that BigData Boutique was the right choice.
The Seamless Move to the Cloud
BigData Boutique were able to deliver a seamless migration to Buzzilla’s new cloud-based infrastructure, hosted on Google Cloud Platform (GCP) and powered by Kubernetes, with zero downtime or disruption experienced. This, Lior was quick to state, was huge for Buzzilla:
“Through a side-by-side deployment with both the data centre and GCP and centralising the logging from the data centre and GCP, Big Data Boutique were able to rapidly prove that the GCP infrastructure was outperforming the on-prem infrastructure, throughout the migration… it was really impressive”.
“I can tell you that, in hindsight, having worked at previous companies with on-premise hosting, the migration process is no easy challenge”, states Lior. BigData Boutique were able to provide this service seamlessly, with zero downtime during the migration.
Modernizing Buzzilla’s Codebase
BigData Boutique addressed some issues with Buzzilla’s code prior to the migration - “we weren’t great at writing code in an organised and forward looking way” notes one Buzzilla employee. Containerization is a vital part of a successful migration of applications to the cloud and often involves decoupling monolithic applications, so they are more fault tolerant during and post-migration.
This modernization of the code exposed many hidden issues within the codebase, some of them existing for years . Such issues were sometimes severe enough to prevent containerization of a specific service, thus making it not cloud-ready. BigData Boutique were able to resolve and rewrite many of these issues, with the new, more maintainable, more visible codebase.
Sharing the knowledge
With paired programming sessions and informed instruction, BigData Boutique were able to get Buzzilla’s developers up to speed on the cutting edge stack, allowing them to be totally self-sufficient when the engagement finished.
BigData Boutique successfully imparted knowledge and expertise, empowering Buzzilla’s developers beyond the scope of their engagement. This piece of work gave Buzzilla a modernised, cloud native application architecture, which is scalable and future-proof.
Enabling search and entity extraction for Hebrew texts
Eyfo is an off-the-shelf set of tools developed by BigData Boutique to solve some of the biggest linguistic and semantic challenges faced by organisations dealing with search and entity extraction. “We integrated Eyfo to enhance our text search and analytics capabilities, and were able to benefit from BigData Boutique’s expertise in entity extraction through this product” Deborah states.
Entity extraction, relating specifically to the Hebrew language, is exceptionally difficult, says Lior:
“When talking about entity extraction, there’s a lot of challenges with [Hebrew] itself: double meanings, morphology, creating specific challenges not found in other languages. When talking about selecting Eyfo as a solution and the associated evaluation process, a developer said “there are not a lot of products on the market that can do it, and there is one that does it very well”.
Observability, monitoring and alerting
We have been able to integrate full end-to-end monitoring, visualizations and health checks in a holistic view to minimize any wider service impacts from third-party downtime. Simple but multi-touchpoint monitoring is of paramount importance for Buzzilla - “we’re now able to collect data and centralize logging from a number of datasources running in the Buzzilla ecosystem”.
A production ready, cost-effective Elasticsearch Cluster
Since Buzzilla’s system is data rich and Elasticsearch is used for many of their search and analytics features over that data, we had to make sure it’s deployed correctly and is as optimized as it can be. We applied our years-long experience for making the most out of the hardware used.
The Elasticsearch cluster topology and its configurations were improved, resulting in performance optimizations, increased resilience, scalability and fewer vulnerabilities. Finally, the Buzzilla codebase was improved to interact more fluidly with the Elasticsearch APIs, incentivizing the engineers to more readily engage with the Elasticsearch cluster and maximise the value gained from this key piece of infrastructure.