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When you build backend systems across dozens of startups, patterns start to emerge.
At TLVTech, speed matters—but so does stability. Startups need to ship fast, iterate without breaking things, and scale without rebuilding their entire backend from scratch.
We’ve refined a tech stack that consistently delivers all three. It’s not about hype—it’s about choosing tools that get out of the way and let teams focus on product.
Here’s the stack we use, why it works, and where we adjust based on use case.
We default to Node.js with TypeScript for most backend services.
Why it works:
We’ll use Python for ML/data pipelines or Go for high-performance cases—but Node/TS is our go-to for API-centric products.
NestJS gives us the best of both worlds: fast setup + enterprise-level structure.
Why it works:
For simpler services, we may go with Express. But NestJS hits the sweet spot for most production backends.
Postgres is rock solid. It's our default unless the use case says otherwise.
Why it works:
We may bring in Redis for caching, MongoDB for unstructured data, or DynamoDB for specific scaling needs—but Postgres carries most of the load.
We build everything container-first.
Why it works:
We adapt based on team size, traffic needs, and deployment maturity—but the principles stay the same.
Simple, integrated, and customizable.
Why it works:
We keep pipelines fast and predictable. Every commit should be shippable. No manual deploys, no broken main branches.
You can’t fix what you can’t see.
Why it works:
We build dashboards that give teams visibility from day one. No waiting for a fire to realize you need alerts.
Startups don’t have time to experiment with unproven tools. This stack lets us move fast, stay clean, and grow without surprises.
If you're building something and want backend speed without technical debt, let’s talk.
- AWS Redshift is a data warehousing service from Amazon Web Services, designed for real-time analysis of large data volumes. - It works by storing data across different compute nodes, creating a high-speed, low-latency network for efficient data exploration. - Data is stored in clusters (groups of databases). Redshift's core functionalities include ETL and integration with most BI tools. - Benefits include scalability, speedy complex queries, and cost-saving. It is valuable for industries like media and healthcare. - Redshift's pay-as-you-go pricing model has two components: node hours and data transfer with costs related to Dense Compute and Dense Storage nodes. - Compared to other platforms, Redshift is superior in scale and performance operations. Redshift is better for complex high-volume analytics, while Athena is suited for simplicity. - To start with Redshift, sign up for an account, select Redshift, follow the setup guide to launch a cluster, load your data, query it, tune when necessary, and manage costs. - Redshift Spectrum is an AWS feature that allows big data manipulation directly from an S3 bucket. It enables data access without loading it into Redshift.
- Agile Testing Life Cycle involves constant testing, integration, and delivery in stages - unit testing, integration testing, functional, and non-functional testing, system testing, and user acceptance testing. - Agile Software Development Life Cycle focuses on smaller cycles with five main components: analysis, design, coding, testing, and deployment. The seven phases of SDLC (planning, requirements, design, build, test, deploy, maintain) fit within this framework. - The bug life cycle in Agile maps the journey of a bug from discovery to resolution. It helps track, manage, and correct software bugs. - The Software Testing Life Cycle (STLC) guides testing tasks with six phases: requirement analysis, test planning, test case development, test environment setup, test execution, test cycle closure. - In Agile STLC, identified and tested new requirements can occur during a current sprint. - The Defect Life Cycle in Agile Software Testing starts when a defect is found and ends with its resolution. Tools like Jira help manage defects by logging, tracking, and alerting team members for prompt action.
