Santa Clara, 95054, CA,
United States
DoiT International
DoiT International, a prominent reseller, system integrator, and consulting company, that plays a vital role in numerous system integration and digital transformation initiatives. DoiT International collaboration with software players such as Google, Amazon Web Services (AWS) and empowers organizations to embrace disruptive technologies and accelerate their journey to the cloud, thus reshaping their business models.
| Reseller and SI | Vendor | Application | Category | Market |
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| DoiT International | Amazon Web Services (AWS) | Amazon Redshift | Data Warehouse | Analytics and BI |
| DoiT International | Google BigQuery | Data Warehouse | Analytics and BI | |
| DoiT International | Google Cloud Dataflow | Application Hosting and Computing Services | IaaS | |
| DoiT International | Google Kubernetes Engine | Container Service | IaaS | |
| DoiT International | Google Cloud Composer | Extract, Transform, and Load (ETL) | PaaS | |
| DoiT International | Google Cloud Dataproc | Analytics and BI | Analytics and BI | |
| DoiT International | Google Cloud Endpoints | API Management | PaaS |
| Logo | Customer | Industry | Empl. | Revenue | Country | Vendor | Product | Category | When | Insight |
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Outbrain | Professional Services | 1016 | $1.0B | United States | Google Cloud Dataproc | Analytics and BI | 2017 |
In 2017 Outbrain planned a migration of its research Hadoop/Spark cluster to Google Cloud Dataproc. The migration to Google Cloud Dataproc, executed starting January 2018, placed the deployment squarely in the Analytics and BI category to support data science and research analytics workloads.
The implementation centered on running Spark research jobs on managed Dataproc clusters with autoscaling enabled and use of preemptible nodes to optimize cost and capacity. Google Cloud Dataproc hosted ephemeral clusters for interactive and batch research workloads, enabling researchers to spin up Spark runtimes and scale compute independently from storage.
Operational scope focused on Outbrain research and data science teams, with a noted acceleration of research project turnaround in Israel. The migration reduced infrastructure costs by approximately 40 percent, an outcome recorded during the post migration period.
Implementation and rollout were driven by DoiT International, which led configuration, provisioning, and operational handoff beginning January 2018 after late 2017 planning. Governance emphasized cloud cost controls and autoscaling policies for Dataproc clusters, aligning platform configuration with research analytics workflows and operational ownership by the data science organization.
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Arabesque Asset Management | Banking and Financial Services | 230 | $60M | United Kingdom | Google Cloud Endpoints | API Management | 2019 |
In 2019 Arabesque Asset Management implemented Google Cloud Endpoints as the API Management layer for its investment analytics and model serving platform on Google Cloud. The initiative centralized API exposure for investment strategies and analytics used by client portals and data distribution services serving customers in the United Kingdom and globally.
Google Cloud Endpoints was configured to expose RESTful and streaming APIs that serve model outputs and analytics pipelines, supporting model-serving endpoints and analytics feeds. Configuration emphasized authentication, traffic management, monitoring, and observability to support high-throughput analytics workloads consistent with API Management capabilities. The deployment leveraged Google Cloud infrastructure for compute and streaming, providing API gateway functionality, request routing, and quota enforcement for production traffic.
DoiT International provided optimization support following deployment, with the migration to Google Cloud reported complete in early 2020. Operational coverage included investment research, quantitative modeling, and client-facing distribution teams, consolidating access to strategy signals and analytics through managed APIs. The case study reports outcomes including approximately 75 percent lower server costs and a tenfold increase in streaming and analysis capacity.
Governance focused on API versioning, access controls for client consumption, and SRE workflows to scale model-serving instances and streaming pipelines. Google Cloud Endpoints functions as the primary API Management control plane for Arabesque's analytics distribution and production model serving.
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Lightricks | Professional Services | 650 | $150M | Israel | Google Cloud Dataflow | Application Hosting and Computing Services | 2022 |
In 2022, Lightricks deployed Google Cloud Dataflow as part of a broader Google Cloud implementation categorized under Application Hosting and Computing Services, using Dataflow together with BigQuery to support high throughput analytics and streaming ingestion. The implementation is explicitly positioned to serve business intelligence, data science, developers, and product teams, and to handle the mobile user behavior telemetry that drives product optimization and recommendation engines.
The technical implementation centered on Google Cloud Dataflow pipelines that automate the ingest and analysis of thousands of events per second, enabling ingestion rates reported at around 10,000 events per second or roughly a billion events per day. BigQuery was used to separate storage from compute, allowing scheduled queries to be prepared minutes before events are registered and making compute resources available on demand. Containerized infrastructure was established on Google Kubernetes Engine in a matter of weeks, and machine learning workloads ran on Compute Engine while a staged migration to Vertex AI was underway to move models to managed services for faster scaling.
Integrations were implemented with BigQuery, Google Kubernetes Engine, Compute Engine, Vertex AI, and external services including Cloudinary and Elasticsearch, with secure traffic forwarding mechanisms that avoid exposure to the public Internet. Lightricks worked with DoiT International on architecture and operational support, including synchronizing on-premises compute and research data lakes with cloud clusters to support model training and inference. Operational coverage included marketing analytics, product optimization, recommendation engine teams, and centralized data platform functions.
The rollout emphasized operational simplicity and governance, reducing infrastructure maintenance overhead so a small engineering and DevOps team could provision clusters and pipelines rapidly. Autoscale in Dataflow removed previous ingestion limits and prevented data blocking, while GKE reduced cluster configuration and upgrade effort and was cited as cost effective for Lightricks workloads. The implementation is described as enabling large scale event processing and machine learning experimentation without inhibiting user experience, and as supporting planned 2022 backend initiatives such as shared profiles and media upload services.
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Professional Services | 3 | $1M | United Kingdom | Google Cloud Composer | Extract, Transform, and Load (ETL) | 2020 |
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Professional Services | 650 | $150M | Israel | Google BigQuery | Data Warehouse | 2020 |
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Professional Services | 650 | $150M | Israel | Amazon Web Services (AWS) | Amazon Redshift | Data Warehouse | 2019 |
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Professional Services | 650 | $150M | Israel | Google Kubernetes Engine | Container Service | 2022 |
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