Mighty Acorn


We stabilize, automate, and accelerate public benefit modernization initiatives by addressing common challenges:

Complex Interdependencies

Modernization initiatives tackle complex services with multiple interdependent legacy systems and little end-to-end visibility into how those systems work.

High uncertainty

Uncertainty about how changes in one system may affect others makes implementing changes difficult and risks disrupting constituents’ experience.

High cost of quality

Extensive manual testing is often required to keep legacy systems up and running while making incremental improvements.

Limited SME availability

Limited availability of subject matter experts needed for testing can create bottlenecks and jeopardize timelines.

Risky deployments

Infrequent releases increase the risk of failure with each deployment.

Eroding stakeholder trust

Without adequate test coverage, responding quickly in the event of a policy change or crisis creates stability issues and erodes stakeholder trust.

We achieve that by enhancing the skills and capabilities of existing teams through:

Technical and Delivery Leadership Consulting

Incubate mature digital service teams that can deliver predictably, adapt appropriately to emerging scope, and meet the needs of the organization and its constituents.

  • Facilitating effective communication between and within teams
  • Improving review processes within teams
  • DevOps, Agile, and Lean practices
  • Building high-trust, generative cultures

Automated End-to-End Testing

Automate the often manual testing of multi-step business processes across more than one system. Tests are built that simulate complex journeys to ensure software is behaving as expected. These automated tests enable additional testing services, such as automating data entry into legacy systems, realistic load testing, and integration testing.

  • For a service that consists of multiple disparate applications working together, automation establishes ongoing visibility into how changes to one system affect another.
  • Silos break down between separate applications when there’s confidence that users can complete their journey all the way from start to finish.

Mock Data Generation and Management

Testing government digital services, like unemployment insurance, often requires realistic mock data to be in place before any testing activities can happen. Building, managing, and clearing mock data across multiple systems, including identity verification, wage/employment records, and authentication is a tedious and time-consuming process.

Automating the process of generating this data eliminates hours of manual effort required to create the large amount of mock data needed for a robust testing program.

Site Reliability Engineering

Site Reliability Engineering (SRE) is the art of making an application as efficient, robust, and resilient to failure as possible. The objective is to improve the reliability of an application, and this is done by observing, replicating, and remediating issues that might otherwise take the service down.

This can take several forms, including:

  • Setup and enhancement of observability tools like New Relic, Splunk, or Cloudwatch
  • Monitoring and alerting on concerning trends before they develop
  • Setting and measuring service level Service Level Objectives (SLOs)
  • Performance remediation (resolving slowness, high resource usage, etc)
  • Reliability remediation (resolving downtime, errors, etc)
  • Architecture recommendations
  • Test automation to uncover reliability issues (load tests, synthetics, etc)

Load Testing

Load testing simulates a digital service under various types of heavy load to identify performance issues and determine monitoring thresholds. This can take the form of basic HTTP request testing, scripted (“end-to-end”) testing, stress testing, breakpoint testing, and soak testing.

The above types of load testing are scripted ”end-to-end”. With this approach to load testing, traffic simulates real-world use cases through an application which often means crossing multiple endpoints. Therefore load is often applied to multiple endpoints at once, and can occasionally involve using an automated web browser for realism.

This provides an opportunity to validate how a service performs “in the real world”, such as during an initial launch. It provides ongoing safety when there’s uncertainty if technical change to a product will impact site reliability.

Copyright © 2024 Mighty Acorn Digital Inc.