AWS Software / SaaS Canada

Ada Support Inc

Application Refactoring · Customer Service Automation

After weighing the options, it chose AWS Global Accelerator —a networking service that organizations use to improve the availability, performance, and security of public applications—because Ada’s engineers could incrementally route traffic to clusters and quickly roll it back if needed.

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Ada’s benchmark automated resolution rates increased from 20–30 percent with declarative agents before the migration to up to 77 percent using generative AI.

By applying the blue/green strategy using Amazon EKS, Ada can upgrade its clusters in 5 days instead of up to 5 months.

In 4 months, with near-zero downtime, Ada completed the migration and several major version upgrades of Kubernetes in 2022.

In the year and a half after the migration, Ada increased the deployment velocity by 70 percent.

Reported impact

Business outcome

Ada plans to continue investing in innovative generative AI features and is considering expanding into other regions, such as Asia Pacific, because of its increased operational efficiency. “Using Amazon EKS, we have much more time to develop and improve product capabilities to deliver a high-quality customer experience,” says Mike Gozzo, chief product and technology officer at Ada. Key reported metrics include In 4 months, with near-zero downtime, Ada completed the migration and several major version upgrades of Kubernetes in 2022.; By applying the blue/green strategy using Amazon EKS, Ada can upgrade its clusters in 5 days instead of up to 5 months.; In the year and a half after the migrati

Solution

In 4 months, with near-zero downtime, Ada completed the migration and several major version upgrades of Kubernetes in 2022. The vast majority of Ada’s workloads, ranging from generic compute to ML workloads, run on Amazon EKS. Because of the huge number of API changes in a multiple-version upgrade, Ada used blue/green deployments —a deployment strategy that creates two separate, identical environments—so that engineers could test changes in isolation. “Using AWS Global Accelerator, we could dial traffic incrementally from 0 to 100 percent with very good granularity,” says Kosta Djukic, principal engineer of cloud infrastructure, Ada. “We could canary-test the new cluster and gain confidence as we added more traffic to Amazon EKS.” Amazon EKS automatically manages the availability and scalability of the Kubernetes control-plane nodes responsible for scheduling containers, managing application availability, storing cluster data, and other key tasks.

Data flow

Source data enters the Ada Support Inc workflow through its application services, processed with Amazon EKS, Amazon EC2, AWS Graviton processors, and delivered through AWS Global Accelerator.

Solution architecture

4 components · 2 layers

Compute
- Amazon EKS Runs containerized workloads and Kubernetes-based application services.
- Amazon EC2 Provides configurable compute capacity for application, training, or inference workloads.
- AWS Graviton processors Improve price performance for compute workloads running on Arm-based instances.
Serving
- AWS Global Accelerator Routes traffic over the AWS backbone for lower-latency global access.

Architecture clues

Ada Architecture Diagram Ada saves time using managed services from AWS, so its engineering team has more time to optimize architecture and deployment pipelines.
Because of the huge number of API changes in a multiple-version upgrade, Ada used blue/green deployments —a deployment strategy that creates two separate, identical environments—so that engineers could test changes in is
For example, Ada set up application sets from Argo CD—an open-source, continuous-delivery tool for Kubernetes—to keep copies of Ada’s applications running across different clusters in sync and efficiently manage differen
In 4 months, with near-zero downtime, Ada completed the migration and several major version upgrades of Kubernetes in 2022.
“Because the migration to Amazon EKS went smoothly, we had time to improve our automated processes and workflows,” says Djukic.
“We could canary-test the new cluster and gain confidence as we added more traffic to Amazon EKS.” Amazon EKS automatically manages the availability and scalability of the Kubernetes control-plane nodes responsible for s

Evidence from the source

Ada’s benchmark automated resolution rates increased from 20–30 percent with declarative agents before the migration to up to 77 percent using generative AI.

By applying the blue/green strategy using Amazon EKS, Ada can upgrade its clusters in 5 days instead of up to 5 months.

In 4 months, with near-zero downtime, Ada completed the migration and several major version upgrades of Kubernetes in 2022.

In the year and a half after the migration, Ada increased the deployment velocity by 70 percent.

With new features, Ada has grown its overall compute footprint by 30 percent since the migration.

Yet, the company reduced compute costs by 15 percent over the same period.

Transparency Evidence & methodology 95/100 reference value · 90% confidence · 2 sources

Review how this reference was scored and trace each normalized claim back to its documented source.

Scoring methodology

How scores are calculated

Customer Reference Value measures usefulness as a customer reference. Evidence Confidence measures the quality and traceability of available evidence, not independent verification.

Customer reference value95/100

Problem clarity20/20
Measures whether the customer's operational problem is specific enough to compare.
Implementation depth20/25
Rewards named components, data flow, integrations, and architecture detail.
Outcome specificity20/20
Measures whether the reported benefit is concrete rather than a generic claim.
Quantified impact25/25
5 metrics describe measurable impact.
Deployment scale10/10
Rewards evidence of a live or scaled deployment and meaningful integration scope.

Evidence confidence90%

Source authority20/25
The main evidence is an official vendor-published customer story.
Claim traceability23/25
11 of 12 key fields link to a named source.
Direct evidence20/20
6 direct source quotes retained.
Date provenance8/10
The publication date comes from publisher-controlled metadata.
Source transparency9/10
2 source references document publisher, URL, authority, retrieval, and supported fields.
Implementation specificity10/10
Rewards source-backed components, data flow, quantified impact, and a specific outcome.

Traceability

Sources & provenance

Field coverage shows which facts each source supports. Dates are shown only when documented by the source.

AWS
Ada Support Inc customer story

First-party
https://aws.amazon.com/solutions/case-studies/ada-support-eks-case-study/

Source type
Vendor-published customer story

Published
Jan 16, 2025
Supports
- Customer
- Business problem
- Solution
- Products
- Solution components
- Data flow
- Integrations
- technical area
- use case category
- Business outcome
- outcome category
- Metrics
- Architecture
- evidence quotes
- Publication date
Built In
Ada Careers, Perks + Culture | Built In

Independent secondary
https://builtin.com/company/ada
The Organization JSON-LD lists addressLocality 'Toronto', addressCountry 'CA', and numberOfEmployees value 421.

Source type
Structured company profile
Supports
- Region

Date evidence

Publisher catalog date Jan 16, 2025 · AWS · First-party
Open date source

Not separately sourced Industry, Company size. Treat these normalized attributes as lower-confidence until a dedicated source is added.

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