Costs, costs, and costs...
Hardal is designed to address server-side cost challenge, utilizing advanced algorithms for efficient tagging cost reduction and insightful traffic and cloud log forecasting.
Server-side tagging is the best method for collecting user interaction data with more enhanced data, more privacy, but costs can be more challenging than switching from client-side to server-side tagging.
Cost Compare of Client-side Tagging vs Server-Side Tagging
| Client-side Tagging | Server-side Tagging |
|---|---|
| Generally less expensive to implement and maintain. | Additional costs may be associated with server-side tracking, including server costs and possibly higher implementation costs. |
| $0 | Depend on your monthly event requests starting from $50 to $$$$ |
Cost Considerations When Transitioning to Server-Side Tagging
- How do you plan to manage your server-side costs to avoid overcharging?
- Are you equipped to optimize resource allocation efficiently?
What is auto revision?
Auto Revision is an ML-based algorithm developed by Hardal that runs daily to forecast previous server-side logs and deploy new revisions with updated configurations, such as CPU, request timeout, and instance numbers on Google Cloud Run and AWS.
That's also how we serve and manage our server-side measurement costs efficiently!
Forecasting Server-Logs
Hardal's standout feature is its ability to forecast future website traffic based on historical data. This allows precise scaling of server resources to meet anticipated demand, avoiding overprovisioning or underestimation.
How it works?
Fetching Previous Period Server-Side Requests
Auto Revision initiates the process by fetching all server-side requests from the previous period. This includes a comprehensive analysis of historical data to gain insights into resource utilization.
Running Algorithm for Cloud Run Auto Revisions on Google Cloud Run or AWS
The heart of Auto Revision lies in its algorithm, which runs on both Google Cloud Run and AWS. This algorithm utilizes the fetched data to forecast future server-side demands. It then dynamically updates configurations, including CPU, request timeout, and instance numbers, optimizing the server infrastructure for efficiency.
Reduction in Server-Side Billable CPU Usage and Requests
Auto Revision process, there is a noticeable reduction in billable server-side CPU usage and requests. This optimization leads to cost-efficiency, ensuring that billable requests start afresh after each revision. Businesses can enjoy the benefits of streamlined resource allocation and reduced costs without compromising performance.
Other Considerations When Transitioning to Server-Side Measurement
Switching your measurement method to server-side brings several considerations into play. Before making the transition, ask yourself these essential questions:
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Monitoring and Maintenance:
- Can you ensure 24/7 monitoring and proper maintenance of server instances?
- Do you have the capability to address unexpected issues promptly?
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Technical Resources:
- Does your business have limited technical resources, and is it suitable for a server-side implementation?
- Is there a dedicated team or external support to handle the technical aspects?
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Security Measures:
- Are you capable of analyzing server-side requests on both Google Cloud Run and AWS to detect and mitigate potential DDoS Attack?
- What security measures will you put in place to safeguard your server-side infrastructure?
These questions are important to check if you're ready to switch to server-side. Thinking about these things helps make sure the change goes well, matching what you can do technically and what your business needs.
Ready to take control of your server-side tagging costs? Sign up for a free trial or request a free demo to experience the new way of server-side tagging, without burnout! 🔥