Customer data is imported into bi(OS) through various mechanisms, some requiring us to expose a public HTTP endpoint. These endpoints are protected against bots. We also record these attack vectors within bi(OS). We built this multi-cloud bot detection capability in 4 weeks using this data. Further, this dynamic list of bots is also made available to all our customers.
The world’s largest eCommerce player uses
Distributed systems are hard. Infrastructure SLAs, sluggish database queries, and microservices latencies must be stitched together to form an accurate view for any eCommerce business. Add agile CI/CD with a Kubernetes-esque control plane, and the fragmented observability toolchain becomes a tax. How does one answer a simple question: are the customer experience (CX) and business KPIs healthy? Well, that’s what […]
I am Saurabh, a Tech Lead at Pharmeasy. My team develops and maintains the ML infrastructure for serving customer recommendations. Last year, we deployed our first real-time recommendation engine for non-Rx product category recommendations on our home page. This blog will explain how Isima’s bi(OS) helped with this initiative and the solution architecture for recommendations.
In the early 90s, Intel ran a campaign about spotting the very best PCs. This decade established Intel as the undisputed leader in microprocessors. 30 years later, engineers at Intel and Isima decided to attempt the same for data and analytics.
Too Long, Must-read The [Live] Multi-cloud-native architecture can deliver a 10X better TCO than the other variants. Some other unique insights we found – Azure’s NVMe drives beat AWS and GCP by a significant amount w.r.to latencies. AWS delivered the most respectable IO latencies when using the best network-attached storage. bi(OS) flips compute utilization for […]
Introduction What happens if the machine, an AZ, or a region serving your customers fails? Nothing – if you rely on cloud-native deployments, stateless microservices, and multi-master databases. That’s the promise anyway. How many IT teams have the luxury of relying on multi-AZ deployments within a cloud? And what about geo-redundancy within a single Cloud? […]
Introduction While the category leaders were busy drowning the market with deafening marketecture(s), our engineers landed on the multi-cloud ‘moon’ of Data and Analytics. TL, DR – Ingest on AWS, Analyze on GCP and Visualize on Azure – in real-time, without migrating an electron. Can your favorite multi-cloud modern data stack do that? That’s the […]
Introduction Since bi(OS) serves unicorns and tier-1 retailers across three continents, we have a unique vantage point in experiencing Black Friday (and Cyber Monday), especially as it stresses Cloud Data Platforms. This Black Friday saw bi(OS) handle 3x more peak load across all tenants, with a near-constant SLA. A day before, a single data stream […]
Introduction Since the birth of SQL in the mid 70’s, there has been a wall of separation between OLTP and OLAP use cases. One of the defining characteristics of this separation is the stringent need for speed and QoS (quality of service) by OLTP applications. Even today, Data Warehouses and Data Lakes pay lip service […]