How applied observability integrate into development process

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Reference no: EM133492712

Discussion Post: Wireless Value Realization and Applied Reliability

Part I:

Wireless Value Realization comes from the rise of vital wireless technologies. Things like Bluetooth, Wi-Fi, and 5g network can be stemmed from wireless value realization. However, with these technologies increasing, so are their capabilities to increase productivity and efficiency by enhancing communications between devices. This also helps businesses reduce production costs with revenue growth and better performance. Although wireless capabilities are nothing new, what's changed is that companies can collect data at a higher and more efficiently. There are other factors to mention with talking about wireless value realization. Here are just a couple:

Cloud computing: Having the ability to store data over the internet, companies can now cut ties with having an on-site infrastructure to save their data. This can cut down the cost it takes to maintain these servers.

Artificial intelligence: Machines can learn natural languages and automate human interactions by collecting specific data much faster than before.

Internet of Things (IoT): refers to connected devices implemented with sensors and software to collect real-time and accurate data. This can be used in healthcare, transportation, and engineering industries.

In summary, wireless value realization is something that is increasingly being used by a vast number of organizations. With new technology like the 5G network, companies increase their productivity by reducing costs. This will make a new impact on how data is being collected and stored. Even with this new technology, I'm sure we're still only scratching the surface of what humans can do with faster and more robust wireless connections.

Part II:

Applied Observability is the study of functional data. Functional data means data that can be used for strategic decision-making. Observability refers to the outcomes of IT systems that can be seen. Applied observability revolves around the application of the output data that these IT systems generate. Most enterprises typically use several systems and tools for information monitoring. After the data is extracted, artificial intelligence can be used to reduce decision making time and increase the value of data through application. (Perri, 2022)

Applied observability has the challenge of being aggregated together. The data needs to be cleaned and understood by the parties attempting to apply it. This can be done by using tools that gather and sort on preprogrammed or customizable rules.

It is vital to know the context of the data being gathered. Some data can be misleading if not understood in the right context. Contextual understanding would help the PEP IT steering committee enable better decision-making. When faced with choices or trade-offs, having a clear understanding of the data's context helps IT professionals make informed decisions. For example, when considering system upgrades, knowing the context allows them to assess the potential impacts, and compatibility with existing components, and evaluate the trade-offs between different options. (Kratzk, 2022)

Contextual information will help the IT steering committee optimize system performance. The IT steering committee can identify bottlenecks, resource constraints, or inefficient processes by analyzing data in the context of the system's configuration, workload, and usage patterns. This knowledge allows them to make informed decisions about capacity planning, resource allocation, and performance tuning to improve the overall efficiency of IT operations.

Task

Question 1. How can applied observability be integrated into the development process?
Question 2. What are the ethical or legal considerations associated with applied observability?
Question 3. What are some additional challenges or opportunities of applied observability?

Reference no: EM133492712

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