The work effort required to complete the list provided for capturing the context of an outcome in an observability dashboard depends on several factors, such as the complexity of the system being monitored, the availability of relevant data, the skill and experience of the team, and the level of integration between observability tools and business data sources. However, to give you a rough estimate, here is a breakdown of the steps and the expected effort:
- Define Desired Outcomes: This step typically involves brainstorming sessions and discussions with various stakeholders, including technical and business teams. Estimated effort: 1-2 days.
- Identify Relevant Metrics: This step requires a deep understanding of the system, its components, and the relationship between technical metrics and business outcomes. Estimated effort: 1-3 days.
- Map Metrics to Outcomes: This step involves creating a clear mapping between the identified metrics and desired outcomes. Estimated effort: 1 day.
- Collect and Aggregate Data: This step may require configuration and customization of observability tools, as well as the development of data pipelines or integrations to aggregate data from different sources. Estimated effort: 1-4 weeks, depending on the complexity of the system and the existing observability infrastructure.
- Visualize Data: Designing an effective dashboard requires an understanding of data visualization principles and the ability to use dashboarding tools. Estimated effort: 1-2 weeks.
- Add Contextual Information: This step involves adding annotations, descriptions, and other contextual information to the dashboard. Estimated effort: 1-3 days.
- Monitor and Adjust: This step is an ongoing process that involves continuous monitoring, analysis, and iteration to ensure the dashboard remains relevant and effective. Estimated effort: ongoing.
Please note that these estimates are approximate and can vary significantly based on the specific circumstances and requirements of your organization. Additionally, some steps may be performed concurrently, potentially reducing the overall time needed to complete the process. It is essential to allocate sufficient time and resources to each step to ensure the successful capture of context in an observability dashboard.
Based on the estimated work effort provided for each step, the total work effort can be summarized as follows:
- Define Desired Outcomes: 1-2 days
- Identify Relevant Metrics: 1-3 days
- Map Metrics to Outcomes: 1 day
- Collect and Aggregate Data: 1-4 weeks (let’s assume an average of 3 weeks or 15 working days)
- Visualize Data: 1-2 weeks (let’s assume an average of 1.5 weeks or 7.5 working days)
- Add Contextual Information: 1-3 days
- Monitor and Adjust: Ongoing (not included in the initial cost estimation)
Total estimated work effort: 26.5-31.5 working days
To estimate the cost of investment, we need to consider the average salary or hourly rate of the professionals involved in this process. Assuming an average hourly rate of $50 for professionals working on this project (you can adjust this rate based on your region and specific circumstances), we can calculate the cost as follows:
Minimum estimated work effort: 26.5 days * 8 hours/day * $100/hour = $21,200
Maximum estimated work effort: 31.5 days * 8 hours/day * $100/hour = $25,200
The estimated cost of investment for capturing the context of an outcome in an observability dashboard ranges from $21,200 to $25,200, excluding the ongoing costs of monitoring and adjusting the dashboard. Keep in mind that these estimates are approximate and can vary depending on factors such as regional salaries, specific project requirements, and the complexity of the system being monitored.
Estimating the ongoing maintenance costs for an observability dashboard depends on various factors, including system complexity, the frequency of updates, and the need for additional resources. Here’s a breakdown of some typical maintenance tasks and their associated costs:
- Dashboard Updates: Updating the dashboard to reflect changes in metrics, business objectives, or system components might be necessary. Estimated effort: 1-2 days per update (assuming quarterly updates, that’s 4-8 days per year).
- Data Pipeline Maintenance: Ensuring data pipelines and integrations remain functional and up-to-date as systems evolve requires ongoing effort. Estimated effort: 1 day per month (12 days per year).
- Monitoring and Analysis: Continuously monitoring the dashboard, analyzing the data, and identifying areas for improvement is an ongoing process. Estimated effort: 1 day per week (approximately 50 days per year).
- Training and Support: Providing training and support for new team members or stakeholders who need to use the dashboard. Estimated effort: variable, depending on the size of the organization and staff turnover.
Using the same average hourly rate of $100 from the previous cost estimation, we can calculate the ongoing maintenance costs:
Minimum estimated work effort: (4 + 12 + 50) days * 8 hours/day * $100/hour = $52,800 per year
Please note that these estimates are approximate and can vary depending on your organization’s specific needs and circumstances. Additionally, this estimate does not account for software licensing or subscription fees for observability tools, data storage, or dashboarding solutions, which may also contribute to ongoing costs.
Estimating the Observability costs:
Estimating the costs of observability licenses and data storage depends on various factors, such as the tools used, the number of users, the volume of data generated, and the data retention period. Here’s a rough breakdown of costs associated with some common observability tools and data storage services:
- Observability Tool Licenses: The costs of observability tools can vary widely depending on the specific product and pricing model. Some common tools and their approximate costs are:
- Datadog: Starts at $15 per host per month for Infrastructure Monitoring and $31 per host per month for APM (Application Performance Monitoring). Pricing varies based on the number of hosts and features.
- New Relic: Starts at $25 per user per month for Full-Stack Observability. Pricing depends on the number of users and features included.
- Dynatrace: Pricing is not publicly available but typically starts at around $20 per host per month. Contact the vendor for a custom quote.
Observability Tool Licenses: Using Datadog for Infrastructure Monitoring and APM for 10 hosts. The approximate annual cost remains $6,720 per year.
- Data Storage: Let’s assume your organization generates 100 TB of observability data per month, which includes logs, metrics, traces, and other contextual information. Using Amazon S3 as an example:
- The first 50 TB per month: $0.023 per GB per month
- The next 450 TB per month: $0.022 per GB per month
Calculating the storage costs for 100 TB (102,400 GB) per month:
- First 50 TB (51,200 GB): (51,200 GB * $0.023) = $1,177.60 per month
- Next 50 TB (51,200 GB): (51,200 GB * $0.022) = $1,126.40 per month
Total cost per month: $1,177.60 + $1,126.40 = $2,304 per month
Total annual cost: $2,304 * 12 months = $27,648 per year
Considering the larger volume of data required for contextual insights, the new estimated costs for observability tool licenses and data storage are:
- Observability tool licenses: $6,720 per year
- Data storage: $27,648 per year
Total estimated annual cost: $34,368
Keep in mind that these are approximate costs based on the example provided and can vary depending on the specific tools, data storage service, data retention policies, and other factors. It’s important to evaluate your organization’s needs and review the pricing details for each tool or service to obtain an accurate estimate of costs.
So the total costs all in are as follows:
Outcome-Centric Dashboard:
$21,200 to Develop
$52,800 to Maintain
$34,368 for licensing and storage
$108,368 total cost of ownership for a small to medium sized business in year one, and $87,168 to keep it going.
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