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.