AWS Cost Reduction Solutions: Elevating Savings with Data Mastery

AWS Cost Reduction

This project optimized the cloud infrastructure of a U.S. IT services company to reduce costs and improve performance. Our investigation identified several areas for optimization, including unused computing resources, inconsistent storage, and a lack of savings plans. We helped to optimize resources, implemented better policies for storage, and improved internal traffic flow through architecture redesigns and dockerization.

DevOps

23k+

monthly savings

8%

performance optimization

About the client

U.S. IT Services and Consulting company that protects businesses and their customers from unauthorized account access, and identity fraud.

Tech stack

AWS

AWS EC2

ECS

Docker

The client's needs

During a period of explosive growth the AWS Cloud infrastructure cost reached 57k per month, this represented an increase of 265% over the last 9 months. A key goal was full cost optimization.

Challenges & solutions

Challenge

To identify areas where costs could be reduced.

Solution

During the discovery, the team investigated the company's cloud infrastructure, including computing resources, storage, and internal traffic flow, to find potential cost reduction targets.

Challenge

Address unused Computing resources:

79% of instances were underused
12% of instances marked as “forgotten”
“Master” instances were continually running instances after CI/CD
No limitations for all company employees when creating instances

Solution

Computing resources:

Optimized instance capacity
Cleaned forgotten instances and resources
Scheduling non-production resources to stop during off-hours
Optimized CI/CD to stop “Master” instances in LB groups
Provided security audit configured with valid permissions for users and groups

Challenge

Volumes/Snapshots/AMI:

31% of volumes got usage below 10%
136 TB of volumes are not attached
No consistency in the storage type

Solution

Volumes/Snapshots/AMI:

Resized underused storage
Backup data to S3 and removed unused volumes
Optimized storage type, downgrade IOPS

Challenge

S3:

No retention policy, data was stored forever
Unused data, a lot of tests, and duplicates
No deep storage for old data (Glasier)

Solution

S3:

Retention policy created
Cleaned unused data and files
Provided Glaser storage

Challenge

Saving plans:

No unified instance families
Use of old instance families
No saving plans enabled

Solution

Saving plans:

Upgraded all instances to the current generation
Chose instance types appropriate for the load
Added reserved instances for stable parts of the infrastructure
Added saving plans for the remaining instances

Challenge

Internal traffic (architecture redesign) is responsible for 7.5% of costs:

Internal services setup as separate EC2 instances
Most data was transferred through a chain of at least 5

Solution

Dockerization:

Microservices dockerized
Running chains of services on the same instance not only fully eliminated data transfer but also increased final performance by 8%.

Challenge

Solution

Challenge

Solution

Results

The results were impressive, with 23.5k in monthly savings, a 67.5% reduction in instance costs, 916 TB of unused storage removed, and an 8% speed improvement. Additionally, the company operates a more secure and robust infrastructure that can handle a doubling of clients with less than 16% cost growth.

‍

The team's deep understanding of our needs allowed us to achieve a more secure, robust, and faster infrastructure that can handle growth without incurring exorbitant costs.

Harris N.

CTO IT Services & Consulting

Steps of providing
data scraping services

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs. At this stage, we need to ensure that we understand the full scope of the project. Receive from you or perform a set of interviews and prepare the following documents: list of features with detailed description and acceptance criteria; list of fields that need to be scraped, solution architecture. Ultimately we make a project plan which we strictly follow. We are a result-oriented company, and that is one of our core values as well.

Step 3 of 5

Solution development

At this stage, we develop the scraping engine core logic. We run multiple tests to ensure that the solution is working properly. We map the fields and run the scraping. While scraping, we keep the full raw data so the final model can be enlarged easily. Ultimately we store data in any database and run quality assurance tests.

Step 4 of 5

Data delivery

After quality assurance tests are completed, we deliver data and solutions to the client. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While developing and crawling data, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

We understand how crucial the solutions that we code for our clients are! Our goal is to build long-term relations, so we provide guarantees and support agreements. What is more, we are always happy to assist with further developments and statistics show that for us, 97% of our clients return to us with new projects.

How we provide data integration solutions

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

At this stage, we need to ensure that we understand the full scope of the project. We receive from you or perform a set of interviews and prepare the following documents: integration pipeline (which data we should get and where to upload), process logic (how system should work); use cases and acceptance criteria; solution architecture. Ultimately we make a project plan which we strictly follow.

Step 3 of 5

Solution development

At this stage, we build ETL pipelines and necessary APIs to automate the process. We attract our DevOps team to build the most efficient and scalable solution. Ending up with unit tests and quality assurance tests to ensure that the solution is working properly. Focus on Results is one of our core values as well.

Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we are expecting client’s participation in the project. While developing the integration system, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

Steps of providing web applications services

Step 1 of 7

Web development discovery

In the initial stage of the web-based development project, professional business analysts make detailed documentation of the project requirements and the approximate structure of the future web application. DATAFOREST is a custom web application development agency, guided by extensive experience in multiple industries. We give you detailed project documentation and then assemble the team according to your time and budget.

Step 2 of 7

UX and UI design

Based on your wishes, the needs of your target audience, and the best web application design and development practices, our UX and UI experts create an aesthetically pleasing and user-friendly interface for your app to satisfy even the most demanding users.

Step 3 of 7

Web-based application development

At DATAFOREST we are following the best programming design principles and approaches. Being a data engineering company, we build high load platforms, with a significant level of flexibility and result orientation. We keep our deadlines and follow SOC 2 compliance requirements.

Step 4 of 7

Integration

With DATAFOREST, integrating the application into your business won’t stop your processes for a minute. We provide seamless integration with your software infrastructure and ensure smooth operation in no time.

Step 5 of 7

Quality assurance

We use a multi-level quality assurance system to avoid any unforeseen issues. Working with DATAFOREST, you can be confident that your web app development service solutions arrive to the market polished and in full compliance with all certification requirements.

Step 6 of 7

24/7 support

Once a product is released to the market, it’s crucial to keep it running smoothly. That’s why our experts provide several models of post-release support to ensure application uptime and stable workflows, increasing user satisfaction.

Step 7 of 7

Web app continuous improvement

Every truly high-quality software product has to constantly evolve to keep up with the times. We understand this, and therefore we provide services for updating and refining our software, as well as introducing new features to meet the growing needs of your business and target audience.

The way we deal with your task and help achieve results

Step 1 of 5

Free consultation

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

In Data Science, there are numerous models and approaches, so at this stage we perform a set of interviews in order to define project objectives. We elaborate and discuss a set of hypotheses and assumptions. We create solution architecture, a project plan, and a list of insights or features that we have to achieve.

Step 3 of 5

Solution development

The work starts with data gathering, data cleaning and analysis. Feature engineering helps to determine your target variable and build several models for the initial review. Further modeling requires validating results and selecting models for the further development. Ultimately, we interpret the results. Nevertheless, data modeling is about a process that requires lots of back and forth iterations. We are result focused, as it’s one of our core values as well.

Step 4 of 5

Solution delivery

Data Science solutions can be a list of insights or a variety of different models that consume data and return results. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. While modeling, we provide midterm results so you can always see where we are and provide us with feedback. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

The way we deal with your issue and achieve result

Free consultation

Step 1 of 5

It's a good time to get info about each other, share values and discuss your project in detail. We will advise you on a solution and try to help to understand if we are a perfect match for you.

Step 2 of 5

Discovering and feasibility analysis

One of our core values is flexibility, hence we work with either one page high level requirements or with a full pack of tech docs.

Depending on project objectives, DevOps activity requires auditing the current approach, running metrics measurement, performing monitoring and checking logs. By having a set of interviews, we ensure that we understand the full scope of the project. Ultimately we make a project plan which we strictly follow. We are a result-oriented DevOps service provider company, and that is one of our core values as well.

Step 3 of 5

Solution development

At this stage, our certified DevOps engineers refine the product backlog. We deliver great results within digital transformation, cost optimization, CI/CD setup, containerization, and, last but not least, monitoring and logging. We are a result focused company – it’s one of our core values.

Step 4 of 5

Solution delivery

After quality assurance tests are completed, we deliver solutions to the client. Though we have over 15 years of expertise in data engineering, we expect client’s participation in the project. By the way, a high-level of communication is also our core value.

Step 5 of 5

Support and continuous improvement

Success stories

Check out a few case studies that show why DATAFOREST will meet your business needs.

All Success Stories

Infrastructure Audit & Intelligent Notifications

An e-commerce company had issues with managing its complex IT infrastructure across multiple cloud providers. We helped to analyze the current architecture and develop a strategy for unification, scaling, monitoring, and notifications. As a result, we implemented a single cloud provider, CI/CD process, server unification, security and vulnerability mitigation actions, and improved reaction speed and reliability by 200%.

200%

performance boost

24/7

monitoring

Dean Schapiro

Co-Founder, CTO Ecom Innovators, E-commerce company

View case study

Not only are they experts in their domains, but they are also provide perfect outcomes.

Performance Optimization & Bottlenecks Elimination

The financial services company faced performance issues and bottlenecks on its financial platform and was looking for a DevOps partner to increase application performance, stability, and resilience, and reduce operational costs. DATAFOREST performed a technical audit of the current AWS infrastructure, created a bottleneck monitoring system, re-developed inefficient SQL queries and data pipelines, and implemented horizontal scaling and a microservice approach using Docker and Kubernetes.

1000%

performance boost

20%

cost optimization

Daniel Garner

CTO Flexium, FinTech company

View case study

Performance Optimization & Bottlenecks Elimination preview

The team of DATAFOREST is very skilled and equipped with high knowledge.

DevOps Experience

The ML startup faced high costs during its growth for a data-driven platform infrastructure that processes around 30 TB per month and stores raw data for 12 months on AWS. We reduced the monthly cost from $75,000 to $22,000 and achieved 30% performance over SLA.

2k+

QPS performance

70%

cost reduction

Robert P.

CTO Cybersecurity

View case study

They have very intelligent people on their team — people that I would gladly hire and pay for myself.

Financial Intermediation Platform

The project aims to develop a deal origination platform for private equity investments in infrastructure-related sectors and involves building a secure, interactive B2B platform from scratch, with sign-up functionality to connect investment firms to proprietary investment opportunities. DATAFOREST built a highly-loaded platform and applied AI functionality to empower the application's development.

98%

model accuracy

100%

timely development