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Hash Functions

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One way functions that transfer character inputs to compressed output value named as hash functions. The input can be infinite(arbitrary), but the output always has a finite(fixed) set of characters. This produces a fingerprint of the file/message/data source: Wikipedia You cannot reverse the function and get the input value in Hash functions. If you have the content, you can use the hash function to calculate the hash value, but the other way around is not possible. If you have the hash value and the function, you can’t use it to get the input text. Below are sample scenarios that hash functions may become useless. If the function is reversible, it’s not secure. Hash values can be exposed to the public. Hence we don’t want someone seeing the hash value. The values may not collision resistant. There may be use cases with two unique input values return the same hash value. Since digital certificates/Signatures using hash fun
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How you can manage throttle out errors in WSO2 API Manager

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You might face the above-mentioned error if you have an application in Dialog Ideabiz platform.Let’s start from the beginning. Once you create an application on Ideabiz, you need to subscribe to the APIs you require. We use WSO2 API manager to manage the APIs . When admin approves your API subscriptions, he/she will assign a tier value for each API(5tps, 10 tps etc.). Also, they will assign a tier value for the application as well. Let’s assume you wanted to create an application by using SMS and Payment API. The team has assigned 5tps for each API and 10tps for your application. You use SMS API only to send SMS to the users and payment API to charge the users on daily basis. When considering each API, (as per above example) you should manage  5 transactions per second in the SMS API. Which means you can have 5 API calls per second. Let’s assume before you send the SMS, you want to charge Rs 1 from the user. Therefore you need to call payment API as well. Since the Pa
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CAP THEOREM

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What’s C, A and P? Consistency is the easiest one. It roughly means that the clients get the same view of data. By saying that a system is consistent we often mean strong consistency, but it also can come in different flavors. Availability is a property saying that every request to a non-failing node will return a (meaningful) response. The response may not contain all data (so the harvest will not be 100%), but it should be useful for the client. Partition tolerance means that the system will continue working even if any number of messages sent between nodes is lost. This can be e.g. a network failure between two data centers, where nodes in each data center form a partition. Also note that a failure of any number of nodes forms a partition (it is not possible to distinguish between a network failure and a node failing and stopping to respond to messages). The basic statement of the CAP theorem is that, given the three properties of Consistency, Availability, and Pa
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